Paper
30 March 1995 Sliding window technique for word recognition
Stephen W. Lam, Anuradha Bhate, Sargur N. Srihari
Author Affiliations +
Proceedings Volume 2422, Document Recognition II; (1995) https://doi.org/10.1117/12.205839
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States
Abstract
The proposed approach addresses the problem of recognition of touching characters by forming a closed loop system between segmentation and isolated character classification for mutually beneficial feedback. Multiple hypotheses are generated and ranked on the basis of various constraints such as classifier confidence, geometric or structural requirements and contextual information at every intermediate step. The method uses a variable width window sliding throughout the word and results in a tree structure with intermediate nodes representing validated characters. Each partial path is assigned a confidence value on the basis of segmentation confidence, recognition confidence and first order transition probability, if applicable. Final candidates for the field truth are ranked according to the value of path confidence. The proposed system is more robust since it uses all the available knowledge sources, including context, run time at every intermediate step.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen W. Lam, Anuradha Bhate, and Sargur N. Srihari "Sliding window technique for word recognition", Proc. SPIE 2422, Document Recognition II, (30 March 1995); https://doi.org/10.1117/12.205839
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Acquisition tracking and pointing

Classification systems

Detection and tracking algorithms

Associative arrays

Image classification

Image quality

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