Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determination of the Script and Language Content of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Script Identification From Document Images Using Cluster-Based Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optical Font Recognition Using Typographical Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Font Recognition Based on Global Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
The Document Spectrum for Page Layout Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optical Font Recognition for Multi-Font OCR and Document Processing
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
Language determination: natural language processing from scanned document images
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Adaptive Hindi OCR using generalized Hausdorff image comparison
ACM Transactions on Asian Language Information Processing (TALIP)
Word level multi-script identification
Pattern Recognition Letters
Combined script and page orientation estimation using the Tesseract OCR engine
Proceedings of the International Workshop on Multilingual OCR
Farsi font recognition based on Sobel-Roberts features
Pattern Recognition Letters
Local features-based script recognition from printed bilingual document images
International Journal of Computer Applications in Technology
Texture feature evaluation for segmentation of historical document images
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
Word level script recognition for Uighur document mixed with English script
Proceedings of the 4th International Workshop on Multilingual OCR
Arabic font recognition based on diacritics features
Pattern Recognition
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When scanning documents with a large number of pagessuch as books, it is often feasible to provide a minimalnumber of training samples to personalize the system tocompensate for global shifts in how the document wascreated or in scanning parameters. In this paper, wepresent a supervised multi-class classifier based onGabor filters that is used to classify the scripts, font-faces,and font-styles (bold, italic, normal etc.) in anapplication where the classes are known. Classificationis performed at the word level (glyphs separated by whitespace) given training samples of each class. This methodwas applied to a variety of bilingual dictionaries toidentify different scripts, and simultaneously, to classifyRoman scripts into bold, italic and normal font-styles.Experimental results show the effectiveness of thisapproach in increasing performance over classifierstrained for general documents.