Automated forms-processing software and services
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Optical Character Recognition for Cursive Handwriting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation-based recognition of handwritten touching pairs of digits using structural features
Pattern Recognition Letters
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ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Improving a bank-check processing system with new HMM-based algorithms
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Design of an Embedded Arabic Optical Character Recognition
Journal of Signal Processing Systems
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This paper provides a review of advances in character segmentation. Segmentation methods are listed under four main headings. The operation of attempting to decompose the image into classifiable units on the basis of general image features is called "dissection". The second class of methods avoids dissection, and segments the image either explicitly, by classification of specified windows, or implicitly by classification of subsets of spatial features collected from the image as a whole. The third strategy is a hybrid of the first two, employing dissection together with recombination rules to define potential segments, but using classification to select from the range of admissible segmentation possibilities offered by these subimages. Finally, holistic approaches that avoid segmentation by recognizing entire character strings as units are described.