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Rotation-invariant texture classification
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Rotation invariant texture classification using even symmetric Gabor filters
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Rotation and scale invariant texture features using discrete wavelet packet transform
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ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
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ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Word level multi-script identification
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Rotation Invariant Texture Classification Using Gabor Wavelets
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DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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This paper concerns the extraction of rotation invariant texture features and the use of such features in script identification from document images. Rotation invariant texture features are computed based on an extension of the popular multi-channel Gabor filtering technique, and their effectiveness is tested with 300 randomly rotated samples of 15 Brodatz textures. These features are then used in an attempt to solve a practical but hitherto mostly overlooked problem in document image processing驴the identification of the script of a machine printed document. Automatic script and language recognition is an essential front-end process for the efficient and correct use of OCR and language translation products in a multilingual environment. Six languages (Chinese, English, Greek, Russian, Persian, and Malayalam) are chosen to demonstrate the potential of such a texture-based approach in script identification.