Visual text recognition through contextual processing
Pattern Recognition
Statistical methods for speech recognition
Statistical methods for speech recognition
Optical Font Recognition Using Typographical Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Omnifont Open-Vocabulary OCR System for English and Arabic
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prototype Extraction and Adaptive OCR
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synthetic Parameters for Handwriting Classification
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Classification Using a Hierarchical Bayesian Approach
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Style-Consistency in Isogenous Patterns
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Style consistency in pattern fields
Style consistency in pattern fields
Training on Severely Degraded Text-Line Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Adaptive classifiers for multisource OCR
International Journal on Document Analysis and Recognition
Style Context with Second-Order Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Style Context with Second-Order Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analytical Results on Style-Constrained Bayesian Classification of Pattern Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document image analysis for digital libraries
Proceedings of the 2006 international workshop on Research issues in digital libraries
Style modeling for tagging personal photo collections
Proceedings of the ACM International Conference on Image and Video Retrieval
Multi-character field recognition for Arabic and Chinese handwriting
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Analysis of whole-book recognition
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Nearest neighbor based collection OCR
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
A quantitative categorization of phonemic dialect features in context
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Modeling context as statistical dependence
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Interactive, mobile, distributed pattern recognition
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
A highly legible CAPTCHA that resists segmentation attacks
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
Towards versatile document analysis systems
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Pattern field classification with style normalized transformation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Estimation, learning, and adaptation: systems that improve with use
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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In many applications of pattern recognition, patterns appear together in groups (fields) that have a common origin. For example, a printed word is usually a field of character patterns printed in the same font. A common origin induces consistency of style in features measured on patterns. The features of patterns co-occurring in a field are statistically dependent because they share the same, albeit unknown, style. Style constrained classifiers achieve higher classification accuracy by modeling such dependence among patterns in a field. Effects of style consistency on the distributions of field-features (concatenation of pattern features) can be modeled by hierarchical mixtures. Each field derives from a mixture of styles, while, within a field, a pattern derives from a class-style conditional mixture of Gaussians. Based on this model, an optimal style constrained classifier processes entire fields of patterns rendered in a consistent but unknown style. In a laboratory experiment, style constrained classification reduced errors on fields of printed digits by nearly 25 percent over singlet classifiers. Longer fields favor our classification method because they furnish more information about the underlying style.