Automated entry system for printed documents
Pattern Recognition
Automatic text recognition for video indexing
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Supervised Template Estimation for Document Image Decoding
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Normalization of Handwritten Characters Using Global/Local Affine Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prototype Extraction and Adaptive OCR
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Telop character extraction from video data
DIA '97 Proceedings of the 1997 Workshop on Document Image Analysis
Robust Telop Character Recognition in Video for Content-Based Retrieval
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Bootstrapping Text Recognition from Stop Words
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Category-Dependent Feature Extraction for Recognition of Degraded Handwritten Characters
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Improvement of Video Text Recognition by Character Selection
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Time-series active search for quick retrieval of audio and video
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Automatic text detection and tracking in digital video
IEEE Transactions on Image Processing
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
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When recognizing multiple fonts, geometric features,such as the directional information of strokes, are generallyrobust against deformation but are weak against degradation.This paper describes a category-dependent feature extractionmethod that uses a feature compensation techniqueto overcome this weakness. Our proposed method estimatesthe degree of degradation of an input pattern by comparingthe input pattern and the template of each category. Thisestimation enables us to compensate the degradation in featurevalues. We apply the proposed method to the recognitionof video text suffering from degradation and deformation.Recognition experiments using characters extractedfrom videos show that the proposed method is superior tothe conventional alternatives in resisting degradation.