Gabor Features Based Script Identification of Lines within a Bilingual/Trilingual Document

The OCR technology for Indian documents is in emerging stage and most of these Indian OCR systems can read the documents written in only a single script. As many commercial and official documents of different states of India are tri-lingual in nature, therefore identification of script and/ or language is one of the elementary tasks for multi-script document recognition. A script recognizer simplifies the task of multi-lingual OCR by improving the accuracy and reducing the computational complexity. This script recognition may be at line, word or character level depending on interlacing of different scripts at different levels. This paper presents the effectiveness of Gabor Filter banks with kNN, SVM and PNN classifiers to identify the scripts at line level from such trilingual documents. The experiments show that Gabor features with SVM classifier achieve a recognition rate of 99.85% for trilingual documents.