Databases for Research on Recognition of Handwritten Characters of Indian Scripts
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Handwritten character recognition using elastic matching and PCA
Proceedings of the International Conference on Advances in Computing, Communication and Control
Recognition of off-line handwritten devnagari characters using quadratic classifier
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Detection of structural concavities in character images--a writer-independent approach
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
Proceeding of the workshop on Document Analysis and Recognition
Applied Computational Intelligence and Soft Computing
Recognition of Bangla compound characters using structural decomposition
Pattern Recognition
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The reading process has been widely studied and there is a general agreement among researchers that knowledge in different forms and at different levels plays a vital role. This is the underlying philosophy of the Devanagari document recognition system described in this work. The knowledge sources we use are mostly statistical in nature or in the form of a word dictionary tailored specifically for optical character recognition (OCR). We do not perform any reasoning on these. However, we explore their relative importance and role in the hierarchy. Some of the knowledge sources are acquired a priori by an automated training process while others are extracted from the text as it is processed. A complete Devanagari OCR system has been designed and tested with real-life printed documents of varying size and font. Most of the documents used were photocopies of the original. A performance of approximately 90% correct recognition is achieved