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Feature extraction implementation for handwritten numeral recognition

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Date Issued:
1994
Summary:
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 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).
Title: Feature extraction implementation for handwritten numeral recognition.
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Name(s): Banuru, Prashanth K.
Florida Atlantic University, Degree grantor
Shankar, Ravi, Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1994
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 155 p.
Language(s): English
Summary: 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 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).
Identifier: 15103 (digitool), FADT15103 (IID), fau:11880 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1994.
Subject(s): Algorithms
Pattern recognition systems--Computer simulation
Optical character recognition devices--Computer simulation
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/15103
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.