Title :
Simple feature extraction for handwritten character recognition
Author :
Pedrazzi, P. ; Colla, A.M.
Author_Institution :
Elsag Bailey-Finmeccanica S.p.A., Genova, Italy
Abstract :
This paper deals with a simple and effective set of features for (handprinted) character representation in automatic reading systems. These features, computed within regularly placed windows spanning the character bitmap, consist of a combination of average pixel density and measures of local alignment along some directions. Patterns from different databases call be accommodated by choosing a variable window size. These features used in conjunction with a neural classifier (MLP) yielded a very high accuracy on several handprinted character databases, including NIST´s ones. Moreover they are easily implementable in VLSI, with throughputs as high as 250,000 characters/sec
Keywords :
VLSI; document image processing; feature extraction; handwriting recognition; image classification; multilayer perceptrons; MLP; NIST; VLSI; automatic reading systems; average pixel density; character bitmap; feature extraction; handprinted character databases; handwritten character recognition; local alignment measures; neural classifier; variable window size; Character recognition; Counting circuits; Feature extraction; NIST; Neural networks; Noise robustness; Optical character recognition software; Throughput; Uncertainty; Very large scale integration;
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
DOI :
10.1109/ICIP.1995.537640
