Segmentation of Overlapping Text Lines, Characters in Printed Telugu Text Document Images

Segmentation is an important task of any OCR system. It separates the image text documents into lines, words and characters. The accuracy of OCR system mainly depends on the segmentation algorithm being used. Segmentation Telugu text is difficult when compared with Latin based languages because of its structural complexity and increased character set. It contains vowels, consonants and compound characters. Some of the characters may overlap together. The profile based methods can only segment non-overlapping lines and characters. This paper addresses the segmentation of overlapped text lines and characters. The proposed algorithm is based on projection profiles, connected components and spatial vertical relationships. It also uses nearest neighborhood method to cluster the connected components. Experimental results it is observed that 100% line segmentation and about 98% character segmentation accuracy can be achieved with overlapping lines and characters.