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Title: HVS-based wavelet color image coding.
Creator: Guo, Linfeng., Florida Atlantic University, Glenn, William E., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This work is an attempt of incorporating the latest advances in vision research and signal processing into the field of image coding. The scope of the dissertation is twofold. Firstly, it sets up a framework of the wavelet color image coder and makes optimizations of its performance. Secondly, it investigates the human vision models and implements human visual properties into the wavelet color image coder. A wavelet image coding framework consisting of image decomposition, coefficients...
Show moreThis work is an attempt of incorporating the latest advances in vision research and signal processing into the field of image coding. The scope of the dissertation is twofold. Firstly, it sets up a framework of the wavelet color image coder and makes optimizations of its performance. Secondly, it investigates the human vision models and implements human visual properties into the wavelet color image coder. A wavelet image coding framework consisting of image decomposition, coefficients quantization, data representation, and entropy coding is first set up, and then a couple of unsolved issues of wavelet image coding are studied and the consequent optimization schemes are presented and applied to the basic framework. These issues include the best wavelet bases selection, quantizer optimization, adaptive probability estimation in arithmetic coding, and the explicit transmission of significant map of wavelet data. Based on the established wavelet image coding framework, a human visual system (HVS) based adaptive color image coding scheme is proposed. Compared with the non-HVS-based coding methods, our method results in a superior performance without any cost of additional side information. As the rudiments of the proposed HVS-based coding scheme, the visual properties of the early stage of human vision are investigated first, especially the contrast sensitivity, the luminance adaptation, and the complicated simultaneous masking and crossed masking effects. To implement these visual properties into the wavelet image coding, the suitable estimation of local background luminance and contrast in the wavelet domain is also re-investigated. Based upon these prerequisite works, the effects of contrast sensitivity weighting and luminance adaptation are incorporated into our coding scheme. Furthermore, the mechanisms of all kinds of masking effects in color image, e.g., the self-masking, the neighbor masking, the crossbands masking, and the luminance-chrominance crossed-masking, are also studied and properly utilized into the coding scheme through an adaptive quantization scheme. Owing to elaborate arrangement and integration of the different parts of the perception based quantization scheme, the coefficient-dependent adaptive quantization step size can be losslessly restored during the decoding without any overhead of side information.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/11941
Subject Headings: Wavelets (Mathematics), Image processing--Digital techniques
Format: Document (PDF)

Title: Selective texture characterization using Gabor filters.
Creator: Boutros, George., Florida Atlantic University, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The objective of this dissertation is to develop effective algorithms for texture characterization, segmentation and labeling that operate selectively to label image textures, using the Gabor representation of signals. These representations are an analog of the spatial frequency tuning characteristics of the visual cortex cells. The Gabor function, of all spatial/spectral signal representations, provides optimal resolution between both domains. A discussion of spatial/spectral representations...
Show moreThe objective of this dissertation is to develop effective algorithms for texture characterization, segmentation and labeling that operate selectively to label image textures, using the Gabor representation of signals. These representations are an analog of the spatial frequency tuning characteristics of the visual cortex cells. The Gabor function, of all spatial/spectral signal representations, provides optimal resolution between both domains. A discussion of spatial/spectral representations focuses on the Gabor function and the biological analog that exists between it and the simple cells of the striate cortex. A simulation generates examples of the use of the Gabor filter as a line detector with synthetic data. Simulations are then presented using Gabor filters for real texture characterization. The Gabor filter spatial and spectral attributes are selectively chosen based on the information from a scale-space image in order to maximize resolution of the characterization process. A variation of probabilistic relaxation that exploits the Gabor filter spatial and spectral attributes is devised, and used to force a consensus of the filter responses for texture characterization. We then perform segmentation of the image using the concept of isolation of low energy states within an image. This iterative smoothing algorithm, operating as a Gabor filter post-processing stage, depends on a line processes discontinuity threshold. Selection of the discontinuity threshold is obtained from the modes of the histogram of the relaxed Gabor filter responses using probabilistic relaxation to detect the significant modes. We test our algorithm on simple synthetic and real textures, then use a more complex natural texture image to test the entire algorithm. Limitations on textural resolution are noted, as well as for the resolution of the image segmentation process.
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Date Issued: 1993
PURL: http://purl.flvc.org/fcla/dt/12342
Subject Headings: Image processing--Digital techniques, Computer vision
Format: Document (PDF)

Title: Subband coding of images using binomial QMF and vector quantization.
Creator: Rajamani, Kannan., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to...
Show moreThis thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to Noise Ratio (SNR) between the original image and the reconstructed image.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15203
Subject Headings: Image compression--Digital techniques, Image processing--Digital techniques, Image transmission--Digital techniques, Coding theory, Vector fields
Format: Document (PDF)

Title: Image retrieval using visual attention.
Creator: Mayron, Liam M., College of Engineering and Computer Science, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The retrieval of digital images is hindered by the semantic gap. The semantic gap is the disparity between a user's high-level interpretation of an image and the information that can be extracted from an image's physical properties. Content based image retrieval systems are particularly vulnerable to the semantic gap due to their reliance on low-level visual features for describing image content. The semantic gap can be narrowed by including high-level, user-generated information. High-level...
Show moreThe retrieval of digital images is hindered by the semantic gap. The semantic gap is the disparity between a user's high-level interpretation of an image and the information that can be extracted from an image's physical properties. Content based image retrieval systems are particularly vulnerable to the semantic gap due to their reliance on low-level visual features for describing image content. The semantic gap can be narrowed by including high-level, user-generated information. High-level descriptions of images are more capable of capturing the semantic meaning of image content, but it is not always practical to collect this information. Thus, both content-based and human-generated information is considered in this work. A content-based method of retrieving images using a computational model of visual attention was proposed, implemented, and evaluated. This work is based on a study of contemporary research in the field of vision science, particularly computational models of bottom-up visual attention. The use of computational models of visual attention to detect salient by design regions of interest in images is investigated. The method is then refined to detect objects of interest in broad image databases that are not necessarily salient by design. An interface for image retrieval, organization, and annotation that is compatible with the attention-based retrieval method has also been implemented. It incorporates the ability to simultaneously execute querying by image content, keyword, and collaborative filtering. The user is central to the design and evaluation of the system. A game was developed to evaluate the entire system, which includes the user, the user interface, and retrieval methods.
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Date Issued: 2008
PURL: http://purl.flvc.org/fcla/flaent/EN00154040/68_1/98p0137i.pdf, http://purl.flvc.org/FAU/58006
Subject Headings: Image processing, Digital techniques, Database systems, Cluster analysis, Multimedia systems
Format: Document (PDF)

Title: Densely-centered uniform P-search: A fast motion estimation algorithm.
Creator: Greenberg, Joshua H., Florida Atlantic University, Furht, Borko
Abstract/Description: Video compression technology promises to be the key to the transmission of motion video. A number of techniques have been introduced in the past few years, particularly that developed by the Motion Picture Experts Group (MPEG). The MPEG algorithm uses Motion Estimation to reduce the amount of data that is stored for each frame. Motion Estimation uses a reference frame as a codebook for a modified Vector Quantization process. While an exhaustive search for Motion Estimation Vectors is time...
Show moreVideo compression technology promises to be the key to the transmission of motion video. A number of techniques have been introduced in the past few years, particularly that developed by the Motion Picture Experts Group (MPEG). The MPEG algorithm uses Motion Estimation to reduce the amount of data that is stored for each frame. Motion Estimation uses a reference frame as a codebook for a modified Vector Quantization process. While an exhaustive search for Motion Estimation Vectors is time-consuming, various fast search algorithms have been developed. These techniques are surveyed, and the theoretical framework for a new search algorithm is developed: Densely-Centered Uniform P-Search. The time complexity of Densely-Centered Uniform P-Search is comparable to other popular Motion Estimation techniques, and shows superior results on a variety of motion video sources.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15286
Subject Headings: Image processing--Digital techniques, Data compression (Telecommunication)
Format: Document (PDF)

Title: Video and Image Analysis using Statistical and Machine Learning Techniques.
Creator: Luo, Qiming, Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Digital videos and images are effective media for capturing spatial and ternporal information in the real world. The rapid growth of digital videos has motivated research aimed at developing effective algorithms, with the objective of obtaining useful information for a variety of application areas, such as security, commerce, medicine, geography, etc. This dissertation presents innovative and practical techniques, based on statistics and machine learning, that address some key research...
Show moreDigital videos and images are effective media for capturing spatial and ternporal information in the real world. The rapid growth of digital videos has motivated research aimed at developing effective algorithms, with the objective of obtaining useful information for a variety of application areas, such as security, commerce, medicine, geography, etc. This dissertation presents innovative and practical techniques, based on statistics and machine learning, that address some key research problems in video and image analysis, including video stabilization, object classification, image segmentation, and video indexing. A novel unsupervised multi-scale color image segmentation algorithm is proposed. The basic idea is to apply mean shift clustering to obtain an over-segmentation, and then merge regions at multiple scales to minimize the MDL criterion. The performance on the Berkeley segmentation benchmark compares favorably with some existing approaches. This algorithm can also operate on one-dimensional feature vectors representing each frame in ocean survey videos, which results in a novel framework for building a hierarchical video index. The advantage is to provide the user with the flexibility of browsing the videos at arbitrary levels of detail, which makes it more efficient for users to browse a long video in order to find interesting information based on the hierarchical index. Also, an empirical study on classification of ships in surveillance videos is presented. A comparative performance study on three classification algorithms is conducted. Based on this study, an effective feature extraction and classification algorithm for classifying ships in coastline surveillance videos is proposed. Finally, an empirical study on video stabilization is presented, which includes a comparative performance study on four motion estimation methods and three motion correction methods. Based on this study, an effective real-time video stabilization algorithm for coastline surveillance is proposed, which involves a novel approach to reduce error accumulation.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012574
Subject Headings: Image processing--Digital techniques, Electronic surveillance, Computational learning theory
Format: Document (PDF)

Title: Low-level and high-level correlation for image registration.
Creator: Mandalia, Anil Dhirajlal., Florida Atlantic University, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The fundamental goal of a machine vision system in the inspection of an assembled printed circuit board is to locate the integrated circuit(IC) components. These components are then checked for their position and orientation with respect to a given position and orientation of the model and to detect deviations. To this end, a method based on a modified two-level correlation scheme is presented in this thesis. In the first level, Low-Level correlation, a modified two-stage template matching...
Show moreThe fundamental goal of a machine vision system in the inspection of an assembled printed circuit board is to locate the integrated circuit(IC) components. These components are then checked for their position and orientation with respect to a given position and orientation of the model and to detect deviations. To this end, a method based on a modified two-level correlation scheme is presented in this thesis. In the first level, Low-Level correlation, a modified two-stage template matching method is proposed. It makes use of the random search techniques, better known as the Monte Carlo method, to speed up the matching process on binarized version of the images. Due to the random search techniques, there is uncertainty involved in the location where the matches are found. In the second level, High-Level correlation, an evidence scheme based on the Dempster-Shafer formalism is presented to resolve the uncertainty. Experiment results performed on a printed circuit board containing mounted integrated components is also presented to demonstrate the validity of the techniques.
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Date Issued: 1990
PURL: http://purl.flvc.org/fcla/dt/14635
Subject Headings: Image processing--Digital techniques, Computer vision, Integrated circuits
Format: Document (PDF)

Title: Bioinformatics-inspired binary image correlation: application to bio-/medical-images, microsarrays, finger-prints and signature classifications.
Creator: Pappusetty, Deepti, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The efforts addressed in this thesis refer to assaying the extent of local features in 2D-images for the purpose of recognition and classification. It is based on comparing a test-image against a template in binary format. It is a bioinformatics-inspired approach pursued and presented as deliverables of this thesis as summarized below: 1. By applying the so-called 'Smith-Waterman (SW) local alignment' and 'Needleman-Wunsch (NW) global alignment' approaches of bioinformatics, a test 2D-image...
Show moreThe efforts addressed in this thesis refer to assaying the extent of local features in 2D-images for the purpose of recognition and classification. It is based on comparing a test-image against a template in binary format. It is a bioinformatics-inspired approach pursued and presented as deliverables of this thesis as summarized below: 1. By applying the so-called 'Smith-Waterman (SW) local alignment' and 'Needleman-Wunsch (NW) global alignment' approaches of bioinformatics, a test 2D-image in binary format is compared against a reference image so as to recognize the differential features that reside locally in the images being compared 2. SW and NW algorithms based binary comparison involves conversion of one-dimensional sequence alignment procedure (indicated traditionally for molecular sequence comparison adopted in bioinformatics) to 2D-image matrix 3. Relevant algorithms specific to computations are implemented as MatLabTM codes 4. Test-images considered are: Real-world bio-/medical-images, synthetic images, microarrays, biometric finger prints (thumb-impressions) and handwritten signatures. Based on the results, conclusions are enumerated and inferences are made with directions for future studies.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3333052
Subject Headings: Bioinformatics, Statistical methods, Diagnostic imaging, Digital techniques, Image processing, Digital techniques, Pattern perception, Data processing, DNA microarrays
Format: Document (PDF)

Title: HEVC optimization in mobile environments.
Creator: Garcia, Ray, Kalva, Hari, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Recently, multimedia applications and their use have grown dramatically in popularity in strong part due to mobile device adoption by the consumer market. Applications, such as video conferencing, have gained popularity. These applications and others have a strong video component that uses the mobile device’s resources. These resources include processing time, network bandwidth, memory use, and battery life. The goal is to reduce the need of these resources by reducing the complexity of the...
Show moreRecently, multimedia applications and their use have grown dramatically in popularity in strong part due to mobile device adoption by the consumer market. Applications, such as video conferencing, have gained popularity. These applications and others have a strong video component that uses the mobile device’s resources. These resources include processing time, network bandwidth, memory use, and battery life. The goal is to reduce the need of these resources by reducing the complexity of the coding process. Mobile devices offer unique characteristics that can be exploited for optimizing video codecs. The combination of small display size, video resolution, and human vision factors, such as acuity, allow encoder optimizations that will not (or minimally) impact subjective quality. The focus of this dissertation is optimizing video services in mobile environments. Industry has begun migrating from H.264 video coding to a more resource intensive but compression efficient High Efficiency Video Coding (HEVC). However, there has been no proper evaluation and optimization of HEVC for mobile environments. Subjective quality evaluations were performed to assess relative quality between H.264 and HEVC. This will allow for better use of device resources and migration to new codecs where it is most useful. Complexity of HEVC is a significant barrier to adoption on mobile devices and complexity reduction methods are necessary. Optimal use of encoding options is needed to maximize quality and compression while minimizing encoding time. Methods for optimizing coding mode selection for HEVC were developed. Complexity of HEVC encoding can be further reduced by exploiting the mismatch between the resolution of the video, resolution of the mobile display, and the ability of the human eyes to acquire and process video under these conditions. The perceptual optimizations developed in this dissertation use the properties of spatial (visual acuity) and temporal information processing (motion perception) to reduce the complexity of HEVC encoding. A unique feature of the proposed methods is that they reduce encoding complexity and encoding time. The proposed HEVC encoder optimization methods reduced encoding time by 21.7% and bitrate by 13.4% with insignificant impact on subjective quality evaluations. These methods can easily be implemented today within HEVC.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004112
Subject Headings: Coding theory, Digital coding -- Data processing, Image processing -- Digital techniques, Multimedia systems, Video compression
Format: Document (PDF)

Title: Realization and implementation of separable-in-denominator two-dimensional digital filter.
Creator: Huang, Ziqiang., Florida Atlantic University, Zilouchian, Ali
Abstract/Description: In this thesis, a partial fraction expansion of a separable-in-denominator 2-D transfer function is given. Based on this expansion, several novel realizations of separable-in-denominator 2-D filter are provide. These realizations have the properties of highly parallel structure and improved throughput delay. The performance figures are given in the tables. A method of evaluation of quantization error of separable-in-denominator 2-D filter is also derived by using the residue method. Formulas...
Show moreIn this thesis, a partial fraction expansion of a separable-in-denominator 2-D transfer function is given. Based on this expansion, several novel realizations of separable-in-denominator 2-D filter are provide. These realizations have the properties of highly parallel structure and improved throughput delay. The performance figures are given in the tables. A method of evaluation of quantization error of separable-in-denominator 2-D filter is also derived by using the residue method. Formulas for calculation of roundoff noise of proposed structures are provided. Two programs which can be used to calculate the roundoff noise of proposed structure are listed in the Appendix. To run the programs, we need only to input the constant coefficients of expanded transfer function. At last, an optimal block realization of separable-in-denominator 2-D filter is discussed and the criterion for the absence of limit cycles for a second-order 2-D block is given.
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Date Issued: 1992
PURL: http://purl.flvc.org/fcla/dt/14879
Subject Headings: Real-time data processing, Image processing--Digital techniques, Electric filters, Digital--Computer programs
Format: Document (PDF)

Title: Using color image processing techniques to improve the performance of content-based image retrieval systems.
Creator: Costa, Fabio Morais., Florida Atlantic University, Furht, Borko
Abstract/Description: A Content-Based Image Retrieval (CBIR) system is a mechanism intended to retrieve a particular image from a large image repository without resorting to any additional information about the image. Query-by-example (QBE) is a technique used by CBIR systems where an image is retrieved from the database based on an example given by the user. The effectiveness of a CBIR system can be measured by two main indicators: how close the retrieved results are to the desired image and how fast we got those...
Show moreA Content-Based Image Retrieval (CBIR) system is a mechanism intended to retrieve a particular image from a large image repository without resorting to any additional information about the image. Query-by-example (QBE) is a technique used by CBIR systems where an image is retrieved from the database based on an example given by the user. The effectiveness of a CBIR system can be measured by two main indicators: how close the retrieved results are to the desired image and how fast we got those results. In this thesis, we implement some classical image processing operations in order to improve the average rank of the desired image, and we also implement two object recognition techniques to improve the subjective quality of the best ranked images. Results of experiments show that the proposed system outperforms an equivalent CBIR system in QBE mode, both from the point of view of precision as well as recall.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12870
Subject Headings: Image processing--Digital techniques, Imaging systems--Image quality, Information storage and retrieval systems
Format: Document (PDF)

Title: Image improvement using dynamic optical low-pass filter.
Creator: Petljanski, Branko., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Professional imaging systems, particularly motion picture cameras, usually employ larger photosites and lower pixel counts than many amateur cameras. This results in the desirable characteristics of improved dynamic range, signal to noise and sensitivity. However, high performance optics often have frequency response characteristics that exceed the Nyquist limit of the sensor, which, if not properly addressed, results in aliasing artifacts in the captured image. Most contemporary still and...
Show moreProfessional imaging systems, particularly motion picture cameras, usually employ larger photosites and lower pixel counts than many amateur cameras. This results in the desirable characteristics of improved dynamic range, signal to noise and sensitivity. However, high performance optics often have frequency response characteristics that exceed the Nyquist limit of the sensor, which, if not properly addressed, results in aliasing artifacts in the captured image. Most contemporary still and video cameras employ various optically birefringent materials as optical low-pass filters (OLPF) in order to minimize aliasing artifacts in the image. Most OLPFs are designed as optical elements with a frequency response that does not change even if the frequency responses of the other elements of the capturing systems are altered. An extended evaluation of currently used birefringent-based OLPFs is provided. In this work, the author proposed and demonstrated the use of a parallel optical window p ositioned between a lens and a sensor as an OLPF. Controlled X- and Y-axes rotations of the optical window during the image exposure results in a manipulation of the system's point-spread function (PSF). Consequently, changing the PSF affects some portions of the frequency components contained in the image formed on the sensor. The system frequency response is evaluated when various window functions are used to shape the lens' PSF, such as rectangle, triangle, Tukey, Gaussian, Blackman-Harris etc. In addition to the ability to change the PSF, this work demonstrated that the PSF can be manipulated dynamically, which allowed us to modify the PSF to counteract any alteration of other optical elements of the capturing system. There are several instances presented in the dissertation in which it is desirable to change the characteristics of an OLPF in a controlled way., In these instances, an OLPF whose characteristics can be altered dynamically results in an improvement of the image quality.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/1927613
Subject Headings: Image processing, Digital techniques, Signal processing, Digital techniques, Frequency response (Dynamics), Polymers and polymerization, Optical wave guides
Format: Document (PDF)

Title: Exploiting audiovisual attention for visual coding.
Creator: Torres, Freddy., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Perceptual video coding has been a promising area during the last years. Increases in compression ratios have been reported by applying foveated video coding techniques where the region of interest (ROI) is selected by using a computational attention model. However, most of the approaches for perceptual video coding only use visual features ignoring the auditory component. In recent physiological studies, it has been demonstrated that auditory stimuli affects our visual perception. In this...
Show morePerceptual video coding has been a promising area during the last years. Increases in compression ratios have been reported by applying foveated video coding techniques where the region of interest (ROI) is selected by using a computational attention model. However, most of the approaches for perceptual video coding only use visual features ignoring the auditory component. In recent physiological studies, it has been demonstrated that auditory stimuli affects our visual perception. In this work, we validate some of those physiological tests using complex video sequence. We designed and developed a web-based tool for video quality measurement. After conducting different experiments, we observed that in the general reaction time to detect video artifacts was higher when video was presented with the audio information. We observed that emotional information in audio guide human attention to particular ROI. We also observed that sound frequency change spatial frequency perception in still images.
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Date Issued: 2013
PURL: http://purl.flvc.org/fcla/dt/3361251
Subject Headings: Digital video, Image processing, Digital techniques, Visual perception, Coding theory, Human-computer interaction, Intersensory effects
Format: Document (PDF)

Title: Adaptive two-level watermarking for binary document images.
Creator: Muharemagic, Edin., Florida Atlantic University, Furht, Borko, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In our society, large volumes of documents are exchanged on a daily basis. Since documents can easily be scanned, modified and reproduced without any loss in quality, unauthorized use and modification of documents is of major concern. An authentication watermark embedded into a document as an invisible, fragile mark can be used to detect illegal document modification. However, the authentication watermark can only be used to determine whether documents have been tampered with, and additional...
Show moreIn our society, large volumes of documents are exchanged on a daily basis. Since documents can easily be scanned, modified and reproduced without any loss in quality, unauthorized use and modification of documents is of major concern. An authentication watermark embedded into a document as an invisible, fragile mark can be used to detect illegal document modification. However, the authentication watermark can only be used to determine whether documents have been tampered with, and additional protection may be needed to prevent unauthorized use and distribution of those documents. A solution to this problem is a two-level, multipurpose watermark. The first level watermark is an authentication mark used to detect document tampering, while the second level watermark is a robust mark, which identifies the legitimate owner and/or user of specific document. This dissertation introduces a new adaptive two-level multipurpose watermarking scheme suitable for binary document images, such as scanned text, figures, engineering and road maps, architectural drawings, music scores, and handwritten text and sketches. This watermarking scheme uses uniform quantization and overlapped embedding to add two watermarks, one robust and the other fragile, into a binary document image. The two embedded watermarks serve different purposes. The robust watermark carries document owner or document user identification, and the fragile watermark confirms document authenticity and helps detect document tampering. Both watermarks can be extracted without accessing the original document image. The proposed watermarking scheme adaptively selects an image partitioning block size to optimize the embedding capacity, the image permutation key to minimize watermark detection error, and the size of local neighborhood in which modification candidate pixels are scored to minimize visible distortion of watermarked documents. Modification candidate pixels are scored using a novel, objective metric called the Structural Neighborhood Distortion Measure (SNDM). Experimental results confirm that this watermarking scheme, which embeds watermarks by modifying image pixels based on their SNDM scores, creates smaller visible document distortion than watermarking schemes which base watermark embedding on any other published pixel scoring method. Document tampering is detected successfully and the robust watermark can be detected even after document tampering renders the fragile watermark undetectable.
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Date Issued: 2004
PURL: http://purl.flvc.org/fau/fd/FADT12113
Subject Headings: Data encryption (Computer science), Computer security, Digital watermarking, Data protection, Image processing--Digital techniques, Watermarks
Format: Document (PDF)

Title: XYZ Video Compression: An algorithm for real-time compression of motion video based upon the three-dimensional discrete cosine transform.
Creator: Westwater, Raymond John., Florida Atlantic University, Furht, Borko, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: XYZ Video Compression denotes a video compression algorithm that operates in three dimensions, without the overhead of motion estimation. The smaller overhead of this algorithm as compared to MPEG and other "standards-based" compression algorithms using motion estimation suggests the suitability of this algorithm to real-time applications. The demonstrated results of compression of standard motion video benchmarks suggest that XYZ Video Compression is not only a faster algorithm, but develops...
Show moreXYZ Video Compression denotes a video compression algorithm that operates in three dimensions, without the overhead of motion estimation. The smaller overhead of this algorithm as compared to MPEG and other "standards-based" compression algorithms using motion estimation suggests the suitability of this algorithm to real-time applications. The demonstrated results of compression of standard motion video benchmarks suggest that XYZ Video Compression is not only a faster algorithm, but develops superior compression ratios as well. The algorithm is based upon the three-dimensional Discrete Cosine Transform (DCT). Pixels are organized as 8 x 8 x 8 cubes by taking 8 x 8 squares out of 8 consecutive frames. A fast three-dimensional transform is applied to each cube, generating 512 DCT coefficients. The energy-packing property of the DCT concentrates the energy in the cube into few coefficients. The DCT coefficients are quantized to maximize the energy concentration at the expense of introduction of a user-determined level of error. A method of adaptive quantization that generates optimal quantizers based upon statistics gathered for the 8 consecutive frames is described. The sensitivity of the human eye to various DCT coefficients is used to modify the quantizers to create a "visually equivalent" cube with still greater energy concentration. Experiments are described that justify choice of Human Visual System factors to be folded into the quantization step. The quantized coefficients are then encoded into a data stream using a method of entropy coding based upon the statistics of the quantized coefficients. The bitstream generated by entropy coding represents the compressed data of the 8 motion video frames, and typically will be compressed at 50:1 at 5% error. The decoding process is the reverse of the encoding process: the bitstream is decoded to generate blocks of quantized DCT coefficients, the DCT coefficients are dequantized, and the Inverse Discrete Cosine Transform is performed on the cube to recover pixel data suitable for display. The elegance of this technique lies in its simplicity, which lends itself to inexpensive implementation of both encoder and decoder. Finally, real-time implementation of the XYZ Compressor/Decompressor is discussed. Experiments are run to determine the effectiveness of the implementation.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/12450
Subject Headings: Digital video, Data compression (Telecommunication), Image processing--Digital techniques, Coding theory
Format: Document (PDF)

Title: Object detection in low resolution video sequences.
Creator: Pava, Diego F., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: With augmenting security concerns and decreasing costs of surveillance and computing equipment, research on automated systems for object detection has been increasing, but the majority of the studies focus their attention on sequences where high resolution objects are present. The main objective of this work is the detection and extraction of information of low resolution objects (e.g. objects that are so far away from the camera that they occupy only tens of pixels) in order to provide a...
Show moreWith augmenting security concerns and decreasing costs of surveillance and computing equipment, research on automated systems for object detection has been increasing, but the majority of the studies focus their attention on sequences where high resolution objects are present. The main objective of this work is the detection and extraction of information of low resolution objects (e.g. objects that are so far away from the camera that they occupy only tens of pixels) in order to provide a base for higher level information operations such as classification and behavioral analysis. The system proposed is composed of four stages (preprocessing, background modeling, information extraction, and post processing) and uses context based region of importance selection, histogram equalization, background subtraction and morphological filtering techniques. The result is a system capable of detecting and tracking low resolution objects in a controlled background scene which can be a base for systems with higher complexity.
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Date Issued: 2009
PURL: http://purl.flvc.org/FAU/186685
Subject Headings: Computer systems, Security measures, Remote sensing, Image processing, Digital techniques, Imaging systems, Mathematical models
Format: Document (PDF)

Title: A novel DSP scheme for image compression and HDTV transmission.
Creator: Dong, Xu., Florida Atlantic University, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The main objective of the research is to develop computationally efficient hybrid coding schemes for the low bit implementations of image frames and image sequences. The basic fractal block coding can compress a relatively low resolution image efficiently without blocky artifacts, but it does not converge well at the high frequency edges. This research proposes a hybrid multi-resolution scheme which combines the advantages of fractal and DCT coding schemes. The fractal coding is applied to...
Show moreThe main objective of the research is to develop computationally efficient hybrid coding schemes for the low bit implementations of image frames and image sequences. The basic fractal block coding can compress a relatively low resolution image efficiently without blocky artifacts, but it does not converge well at the high frequency edges. This research proposes a hybrid multi-resolution scheme which combines the advantages of fractal and DCT coding schemes. The fractal coding is applied to get a lower resolution, quarter size output image and DCT is then used to encode the error residual between original full bandwidth image signal and the fractal decoded image signal. At the decoder side, the full resolution, full size reproduced image is generated by adding decoded error image to the decoded fractal image. Also, the lower resolution, quarter size output image is automatically given by the iteration function scheme without having to spend extra effort. Other advantages of the scheme are that the high resolution layer is generated by error image which covers the bandwidth loss of the lower resolution layer as well as the coding error of the lower resolution layer, and that it does not need a sophisticated classification procedure. A series of computer simulation experiments are conducted and their results are presented to illustrate the merit of the scheme. The hybrid fractal coding method is then extended to process motion sequences as well. A new scheme is proposed for motion vector detection and motion compensation, by judiciously combining the techniques of fractal compression and block matching. The advantage of this scheme is that it improves the performance of the motion compensation, while keeping the overall computational complexity low for each frame. The simulation results on realistic video conference image sequences support the superiority of the proposed method in terms of reproduced picture quality and compression ratio.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/12407
Subject Headings: Hybrid integrated circuits, Image compression, Fractals, Image processing--Digital techniques, High definition television
Format: Document (PDF)

Title: Event detection in surveillance video.
Creator: Castellanos Jimenez, Ricardo Augusto., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Digital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video...
Show moreDigital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video sequences. This thesis presents a surveillance system based on optical flow and background subtraction concepts to detect events based on a motion analysis, using an event probability zone definition. Advantages, limitations, capabilities and possible solution alternatives are also discussed. The result is a system capable of detecting events of objects moving in opposing direction to a predefined condition or running in the scene, with precision greater than 50% and recall greater than 80%.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/1870694
Subject Headings: Computer systems, Security measures, Image processing, Digital techniques, Imaging systems, Mathematical models, Pattern recognition systems, Computer vision, Digital video
Format: Document (PDF)

Title: Content identification using video tomography.
Creator: Leon, Gustavo A., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Video identification or copy detection is a challenging problem and is becoming increasingly important with the popularity of online video services. The problem addressed in this thesis is the identification of a given video clip in a given set of videos. For a given query video, the system returns all the instance of the video in the data set. This identification system uses video signatures based on video tomography. A robust and low complexity video signature is designed and implemented....
Show moreVideo identification or copy detection is a challenging problem and is becoming increasingly important with the popularity of online video services. The problem addressed in this thesis is the identification of a given video clip in a given set of videos. For a given query video, the system returns all the instance of the video in the data set. This identification system uses video signatures based on video tomography. A robust and low complexity video signature is designed and implemented. The nature of the signature makes it independent to the most commonly video transformations. The signatures are generated for video shots and not individual frames, resulting in a compact signature of 64 bytes per video shot. The signatures are matched using simple Euclidean distance metric. The results show that videos can be identified with 100% recall and over 93% precision. The experiments included several transformations on videos.
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Date Issued: 2008
PURL: http://purl.flvc.org/FAU/2783207
Subject Headings: Biometric identification, High performance computing, Image processing, Digital techniques, Multimedia systems, Security measures
Format: Document (PDF)

Title: A Novel Method for Human Face Enhancement for Video Images.
Creator: Salas, Ernesto Anel, Pandya, Abhijit S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The focus of this research is on images extracted from surveillance videos that have a low resolution and are taken under low illumination. In recent years, great advances have been made in face recognition and many studies mention results of 80% and 90% of recognition efficiency, however, most of these studies reported results using face images under controlled conditions. Current surveillance systems are equipped with low resolution cameras and are located in places with changing...
Show moreThe focus of this research is on images extracted from surveillance videos that have a low resolution and are taken under low illumination. In recent years, great advances have been made in face recognition and many studies mention results of 80% and 90% of recognition efficiency, however, most of these studies reported results using face images under controlled conditions. Current surveillance systems are equipped with low resolution cameras and are located in places with changing illumination, as opposed to a controlled environment. To be used in face recognition, images extracted from videos need to be normalized, enlarged and preprocessed. There is a multitude of processing algorithms for image enhancement, and each algorithm faces its advantages and disadvantages. This thesis presents a novel method for image enlargement of human faces applied to low quality video recordings. Results and comparison to traditional methods are also presented.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012547
Subject Headings: Human face recognition (Computer science), Biometric identification, Image processing--Digital techniques, Pattern recognition systems
Format: Document (PDF)

Image processing--Digital techniques (21)	+ -
Digital techniques (9)	+ -
Image processing (9)	+ -
Coding theory (4)	+ -
Computer vision (4)	+ -

Pattern recognition systems (4)	+ -
Biometric identification (3)	+ -
Digital video (3)	+ -
Multimedia systems (3)	+ -
Remote sensing (3)	+ -
Security measures (3)	+ -
Computer algorithms (2)	+ -
Computer systems (2)	+ -
Data compression (Telecommunication) (2)	+ -
Data encryption (Computer science) (2)	+ -
Human face recognition (Computer science) (2)	+ -
Human-computer interaction (2)	+ -
Image processing -- Digital techniques (2)	+ -
Imaging systems (2)	+ -
Information storage and retrieval systems (2)	+ -
Mathematical models (2)	+ -
Optical character recognition devices (2)	+ -
Video compression (2)	+ -
Visual perception (2)	+ -
Approximation theory -- Mathematical models (1)	+ -
Artificial intelligence (1)	+ -
Artificial intelligence. (1)	+ -
Bioinformatics (1)	+ -
Cities and towns (1)	+ -
Cluster analysis (1)	+ -

College of Engineering and Computer Science (27)	+ -
Department of Computer and Electrical Engineering and Computer Science (26)	+ -
Florida Atlantic University (26)	+ -
Furht, Borko (5)	+ -
Marques, Oge (4)	+ -

Sudhakar, Raghavan (3)	+ -
Charles E. Schmidt College of Science (2)	+ -
Erdol, Nurgun (2)	+ -
Pandya, Abhijit S. (2)	+ -
BEGUN, RALPH MURRAY. (1)	+ -
Barenholtz, Elan (1)	+ -
Boutros, George. (1)	+ -
Castellanos Jimenez, Ricardo Augusto. (1)	+ -
Center for Complex Systems and Brain Sciences (1)	+ -
Costa, Fabio Morais. (1)	+ -
Department of Geosciences (1)	+ -
Department of Ocean and Mechanical Engineering (1)	+ -
Dong, Xu. (1)	+ -
Frisk, George V. (1)	+ -
Gammack-Clark, James Peter (1)	+ -
Garcia, Ray (1)	+ -
Gibson, Joel (1)	+ -
Glenn, William E. (1)	+ -
Greenberg, Joshua H. (1)	+ -
Guo, Linfeng. (1)	+ -
Hahn, William E. (1)	+ -
Huang, Ziqiang. (1)	+ -
James, Jhanon (1)	+ -
Johnson, Brian A. (1)	+ -
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