Automatic separation of words in multi-lingual multi-script Indian documents

In a multi-lingual country like India, a document may contain more than one script forms. For such a document it is necessary to separate different script forms before feeding them to OCRs of individual script. In this paper an automatic word segmentation approach is described which can separate Roman, Bangla and Devnagari scripts present in a single document. The approach has a tree structure where at first Roman script words are separated using the 'headline' feature. The headline is common in Bangla and Devnagari but absent in Roman. Next, Bangla and Devnagari words are separated using some finer characteristics of the character set although recognition of individual character is avoided. At present, the system has an overall accuracy of 96.09%.

[1]  Bidyut Baran Chaudhuri,et al.  An OCR system to read two Indian language scripts: Bangla and Devnagari (Hindi) , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[2]  Theodosios Pavlidis,et al.  On the Recognition of Printed Characters of Any Font and Size , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  AZRIEL ROSENFELD,et al.  Digital Straight Line Segments , 1974, IEEE Transactions on Computers.

[4]  Bidyut Baran Chaudhuri,et al.  Skew Angle Detection of Digitized Indian Script Documents , 1997, IEEE Trans. Pattern Anal. Mach. Intell..