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Automatic identification of English, Chinese, Arabic, Devnagari and Bangla script line

U. Pal , B.B. Chaudhuri

In a general situation, a document page may contain several scriptforms. For optical character recognition (OCR) of such a document page, it is necessary to separate the scripts before feeding them to their individual OCR systems. An automatic technique for the identification of printed Roman, Chinese, Arabic, Devnagari and Bangla text lines from a single document is proposed. Shape based features, statistical features and some features obtained from the concept of a water reservoir are used for script identification. The proposed scheme has an accuracy of about 97.33%.

OCR in Bangla: an Indo-Bangladeshi Language

U. Pal ; B.B. Chaudhuri

In this paper a complete OCR system is described for documents of single Bangla (Bengali) font. The character shapes are recognized by a combination of template and feature matching approach. Images digitized by flatbed scanner are subjected to skew correction, line, word and character segmentation, simple and compound character separation, feature extraction and finally character recognition. A feature based tree classifier is used for simple character recognition. Preprocessing like thinning and skeletonization is not necessary in our scheme and hence the system is quite fast. At present, the system has an accuracy of about 96%. Also, some character occurrence statistics have been computed to model an error detection and correction technique in the near future.

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