Title :
Off-line handwriting recognition from forms
Author :
Garris, Michael D. ; Blue, James L. ; Candela, Gerald T. ; Dimmick, Darrin L. ; Geist, Jon ; Grother, Patrick J. ; Janet, Stanley A. ; Wilson, Charles L.
Author_Institution :
Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
Abstract :
A public domain optical character recognition (OCR) system has been developed by the National Institute of Standards and Technology (NIST) to provide a baseline of performance on off-line handwriting recognition from forms. The system´s source code, training data, and performance assessment tools are all publicly available. The system recognizes the handprint written on handwriting sample forms as distributed on the CD-ROM, NIST Special Database 19. The public domain package contains a number of significant contributions to OCR technology, including an optimized probabilistic neural network classifier that operates a factor of 20 times faster than traditional software implementations of this algorithm. The modular design of the software makes it useful for training and testing set validation, multiple system voting schemes, and component evaluation and comparison. As an example, the OCR results from two versions of the recognition system are presented and analyzed
Keywords :
handwriting recognition; image classification; learning systems; neural nets; optical character recognition; public domain software; NIST Special Database 19; National Institute of Standards and Technology; neural classifier; off-line handwritten character recognition; probabilistic neural network; public domain OCR; CD-ROMs; Character recognition; Distributed databases; Handwriting recognition; NIST; Neural networks; Optical character recognition software; Packaging; Software packages; Training data;
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
DOI :
10.1109/ICSMC.1995.538203
