The nature of statistical learning theory
The nature of statistical learning theory
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Are Multilayer Perceptrons Adequate for Pattern Recognition and Verification?
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Touching numeral segmentation using water reservoir concept
Pattern Recognition Letters
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Reducing the classification cost of support vector classifiers through an ROC-based reject rule
Pattern Analysis & Applications
A Recognition Based System for Segmentation of Touching Handwritten Numeral Strings
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Automatic Segmentation of Unconstrained Handwritten Numeral Strings
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
A Synthetic Database to Assess Segmentation Algorithms
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Optimising two-stage recognition systems
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Binary segmentation with neural validation for cursive handwriting recognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Segment confidence-based binary segmentation (SCBS) for cursive handwritten words
Expert Systems with Applications: An International Journal
Segmentation strategy of handwritten connected digits (SSHCD)
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
Binary segmentation algorithm for English cursive handwriting recognition
Pattern Recognition
Assessing handwitten digit segmentation algorithms
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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In this paper we propose a method to evaluate segmentation cuts for handwritten touching digits. The idea of this method is to work as a filter in segmentation-based recognition system. This kind of system usually rely on over-segmentation methods, where several segmentation hypotheses are created for each touching group of digits and then assessed by a general-purpose classifier. The novelty of the proposed methodology lies in the fact that unnecessary segmentation cuts can be identified without any attempt of classification by a general-purpose classifier, reducing the number of paths in a segmentation graph, what can consequently lead to a reduction in computational cost. An cost-based approach using ROC (receiver operating characteristics) was deployed to optimize the filter. Experimental results show that the filter can eliminate up to 83% of the unnecessary segmentation hypothesis and increase the overall performance of the system.