Current Search: Banuru, Prashanth K. (x)
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Title
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Feature extraction implementation for handwritten numeral recognition.
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Creator
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Banuru, Prashanth K., Florida Atlantic University, Shankar, Ravi
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Abstract/Description
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Feature extraction for handwritten character recognition has always been a challenging problem for investigators in the field. The problem gets worse due to large variations present for each type of input character. Our algorithm computes directional features for alphanumeric input mapped on to a hexagonal lattice. The algorithm implements size and scale invariance that is a requirement for achieving a reasonably good recognition rate. Functional performance has been verified for an hexagonal...
Show moreFeature extraction for handwritten character recognition has always been a challenging problem for investigators in the field. The problem gets worse due to large variations present for each type of input character. Our algorithm computes directional features for alphanumeric input mapped on to a hexagonal lattice. The algorithm implements size and scale invariance that is a requirement for achieving a reasonably good recognition rate. Functional performance has been verified for an hexagonal lattice mapped input on the data obtained from the US postal service handwritten character database. In this thesis, we implemented the algorithm in a Xilinx FPGA (XC4xxx series).
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Date Issued
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1994
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PURL
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http://purl.flvc.org/fcla/dt/15103
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Subject Headings
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Algorithms, Pattern recognition systems--Computer simulation, Optical character recognition devices--Computer simulation
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Format
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Document (PDF)
