Issue No. 07 - July (1998 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.689305
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-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.
image texture, document image processing, spatial filters, feature extraction, language translation, optical character recognition, texture-based approach, rotation invariant texture features, automatic script identification, document images, multi-channel Gabor filtering technique, Brodatz textures, machine printed document, language recognition, language translation, multilingual environment, Chinese, English, Greek, Russian, Persian, Malayalam, Optical character recognition software, Natural languages, Filtering, Image texture analysis, Humans, Energy measurement, Gabor filters, Testing, Feature extraction, Image recognition
"Rotation invariant texture features and their use in automatic script identification," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 751,752,753,754,755,756, 1998.