Texture Classification Using Rotation- and Scale-Invariant Gabor Texture Features
Script identification is an important step in success of multilingual OCR with specialized OCR for each script. Language like Kannada has a wide variety of font style and OCR for Kannada should handle all font type. A multi-OCR with specialized recognizer for each font type is most suitable for Kannada script. Font type identification is a key step in such as solution. We have proposed font identification technique using Gabor features on sub image level. Representatives of Gabor feature are formed and a confidence measure based on Euclidean distance is used as closeness measure. A bin is used which keep track of highest confidence occur at word level and based on maximum bin count font type of a document is identified. Experiments are conducted on scanned Kannada document with 100% as font type identification rate at document level.