Analytical Results on Style-Constrained Bayesian Classification of Pattern Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-character field recognition for Arabic and Chinese handwriting
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Proceedings of the 10th ACM symposium on Document engineering
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Modern adaptive thresholding algorithms do their best to provide good quality binarized images. Unfortunately, it's hard to find a good compromise between the amount of background noise in the binary result and the amount of breaks or missing parts in the shape of characters if the original grey image has low contrast.In this paper we describe some voting methods starting from an external, "black box" voter, to a more deeply integrated "shape" voter that can be used to generate even better recognition results by running a voting OCR engine on two, differently thresholded, images.