Confidence-Scoring Post-Processing for Off-Line Handwritten-Character Recognition Verification
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Confidence Measures for an Address Reading System
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Recognition and Verification of Unconstrained Handwritten Words
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rejection strategies for offline handwritten text line recognition
Pattern Recognition Letters
Rejection strategies for offline handwritten text line recognition
Pattern Recognition Letters
Rejection Strategies Involving Classifier Combination for Handwriting Recognition
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
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We apply confidence-scoring techniques to verify the output of a handwriting recognizer. We evaluate a variety of scoring functions, including likelihood ratios and estimated posterior probabilities of correctness, in a post-processing mode to generate confidence scores at the character or word level. Using the post-processor in conjunction with an HMM-based on-line handwriting recognizer for large-vocabulary word recognition, receiver-operating-characteristic(ROC) curves reveal that our post-processor is able to reject correctly 90% of recognizer errors while only falsely rejecting 33% of correctly-recognized words. For isolated-digit recognition, we achieve a correct rejection rate of 90% while keeping false rejection down to 13%.