Text categorization using character shape codes

Text categorization in the form of topic identification is a capability of current interest. This paper is concerned with categorization of electronic document images. Previous work on the categorization of document images has relied on Optical Character Recognition (OCR) to provide the transformation between the image domain and a domain where pattern recognition techniques are more readily applied. Our work uses a different technology to provide this transformation. Character shape coding is a computationally efficient, extraordinarily robust, means of providing access to the character content of document images. While this transform is lossy, sufficient salient information is retained to support many applications. Furthermore, the use of shape coding is particularly advantageous over OCR in the processing of page images of poor quality. In this study we found that topic identification performance was maintained or slightly improved using character shape codes derived from images.