Systems and methods for style conscious field classification

Image analysis – Pattern recognition – Classification

Reexamination Certificate

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Reexamination Certificate

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10324151

ABSTRACT:
Techniques are provided to classify patterns in isogenous pattern sources. Techniques are provided to determine a computationally inexpensive upperbound on the true score or joint probability of the field label and field features over all field labels. Candidate field labels associated with promising upperbound scores are dynamically queued. True scores are computed for a subset of the candidates fields resulting in reduced computations to determine a field label. Techniques are also provided to determine optimal variables for any system with shared constraints.

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patent: 6678418 (2004-01-01), Chen
Sarkar et al., “Classification of Style-Constrained Pattern-Fields”, Proceedings of the 15th ICPR, vol. 2, pp. 859-862, Barcelona, Sep. 2000.
Sarkar et al., “Style Consistency in Isogenous Patterns” in Proceedings of the 15th ICPR, vol. 2, pp. 859-862, Barcelona, Sep. 2000.
Sarkar et al., “Triage of OCR Results Using ‘Confidence’ Scores” In Proceedings of SPIE/IS&T 2002 Document Recognition & Retrieval IX Conf. (DR&R IX), San Jose, CA Jan. 2002.
Prateek Sarkar, “Style Consistency in Pattern Fields” Rennselaer Polytechnic Institute, Ph.D. Thesis, Troy, NY, 2000.
Prateek Sarkar et al., “Style Consistency in Isogenous Patterns” in Proceedings of the Sixth International Conference for Pattern Recognition, pp. 1169-1174, Seattle, WA, Sep. 2001.
Prateek Sarkar, An Iterative Algorithm for Optimal Style Conscious Field Classification (ICPR'02), in Proceedings of the 16th International Conference on Pattern Recognition, vol. 4, p. 40243, IEEE Computer Society, Quebec City, Canada, 2002.
Prateek Sarkar et al., “Classification of style-constrained pattern-fields”, in Proceedings of the 15th ICPR, pp. 859-862, IEEE Computer Society Press, Barcelona, 2000.
Prateek Sarkar, “Style Consistent Classification of Isogenous Patterns” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, No. 1, pp. 88-98, Jan. 2005.

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