Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Impacts of verification on a numeral string recognition system
Pattern Recognition Letters - Special issue: Sibgrapi 2001
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Recognition and Verification of Unconstrained Handwritten Words
IEEE Transactions on Pattern Analysis and Machine Intelligence
An implicit segmentation-based method for recognition of handwritten strings of characters
Proceedings of the 2006 ACM symposium on Applied computing
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
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Abstract: In this paper we propose a handwritten numeral string recognition method composed of two HMM-based stages. The first stage uses an implicit segmentation strategy based on string contextual information to provide multiple segmentation-recognition paths. These paths are verified and re-ranked by using a Verification stage based on a digit classifier. It allows the use of two sets of features and numeral models: one taking into account of both segmentation and recognition aspects in an implicit segmentation based strategy, and another considering just recognition aspects of isolated digits. The two system stages have shown to be complementary in the sense that the Verification stage has shown to be a promising idea to deal with the loss in terms of recognition performance brought by the necessary tradeoff between segmentation and recognition carried out in the first system stage.