ROTATION-INVARIANT TEXTURE FEATURES AND THEIR USE IN AUTOMATIC SCRIPTIDENTIFICATION

This paper concerns the extraction of rotation invariant texture featu res and the use of such features in script identification from documen t 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 docum ent. Automatic script and language recognition is an essential front-e nd process for the efficient and correct use of OCR and language trans lation products in a multilingual environment. Six languages (Chinese, English, Greek, Russian, Persian, and Malayalam) are chosen to demons trate the potential of such a texture-based approach in script identif ication.