학술논문
Simple feature extraction for handwritten character recognition
Document Type
Conference
Author
Source
Proceedings., International Conference on Image Processing Image processing Image Processing, 1995. Proceedings., International Conference on. 3:320-323 vol.3 1995
Subject
Language
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.