An interpretive model of line continuation in human visual perception
Pattern Recognition
Character image enhancement by selective region-growing
Pattern Recognition Letters
A Survey of Methods and Strategies in Character Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Practical Image Processing in C: Acquisition, Manipulation, Storage
Practical Image Processing in C: Acquisition, Manipulation, Storage
Character Recognition Without Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Reconstruction of Damaged Character Images on the Form Documents
GREC '97 Selected Papers from the Second International Workshop on Graphics Recognition, Algorithms and Systems
Graph-based handwritten digit string recognition
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
A New Scheme for Off-Line Handwritten Connected Digit Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
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We propose a model for the recognition of unconstrained digits that may be touched with neighbor ones or damaged by noises such as lines. The recognition of such digits seems to be rather paradoxical because it requires the segmentation of them into understandable units, but proper segmentation needs a priori knowledge of the units and this implies recognition capability. To break up the loop of their interdependencies, we combine two schemes, hypothesis testing and data reconstruction, motivated by the human information system. Hypothesis is set up on the basis of the information obtained from the results of the basic segmentation, and reconstruction of the information is carried out with the knowledge of a guessed digit and then testing for its validity is performed. Since our model tries to construct a guessed digit from input image it can be successful in a variety of situations such as that a digit contains strokes that do not belong to to it, that neighbor digits are touched with each other, and that there are some occluding things like lines. The recognition results of this model for 100 handwritten numeral strings belonging to NIST database and for some artificial digits damaged by line demonstrate the potential its capacity.