The nature of statistical learning theory
The nature of statistical learning theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
TextFinder: An Automatic System to Detect and Recognize Text In Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural network-based text location in color images
Pattern Recognition Letters
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Video OCR for Digital News Archive
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Automatic Text Extraction from Video for Content-Based Annotation and Retrieval
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Optimized Gabor Filter Based Feature Extraction for Character Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Text Enhancement with Asymmetric Filter for Video OCR
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
ICDAR 2003 Robust Reading Competitions
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Text Locating Competition Results
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Two-Stage License Plate Detection Using Gentle Adaboost and SIFT-SVM
ACIIDS '09 Proceedings of the 2009 First Asian Conference on Intelligent Information and Database Systems
Text Detection and Localization in Complex Scene Images using Constrained AdaBoost Algorithm
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Text Localization in Natural Scene Images Based on Conditional Random Field
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Detecting and reading text in natural scenes
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Pattern Recognition 1966 IEEE Workshop
IEEE Spectrum
Classification of handprinted Kanji characters by the structured segment matching method
Pattern Recognition Letters
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For the Chinese text location under complex background, this paper presents a novel method by combining Gabor filter and support vector machine (SVM). It bases on such a fact that Chinese characters are composed of four kinds of strokes. By extracting four kinds of stroke features with Gabor filters, Chinese text location problem can be transformed into a texture classification one, which can use SVM classifier for the purpose. So, the proposed method is composed of two phases. First, Gabor filters with different scales and orientations are employed to obtain four texture images representing the stokes of Chinese text in horizontal line, top-down vertical line, left-downward slope line and short pausing stroke directions. Then, the text regions and background regions in four texture images are used to train four SVM classifiers to distinguish the texture in four directions, by integrating an SVM classification network to obtain the final classification results, according to the sum of the weights to determine whether the block is the text region. Some experiments are conducted on a large amount of typical images with different texts and different fonts. Compared with some existing methods, the proposed approach achieves better results for Chinese text location.