DocumentCode :
3580483
Title :
Line, Word, and Character Segmentation of Manipuri Machine Printed Text
Author :
Nath, Keshab ; Jelil, Sarfaraz ; Rahul, Laishram
Author_Institution :
Dept. of Inf. Technol., Assam Univ., Silchar, India
fYear :
2014
Firstpage :
203
Lastpage :
206
Abstract :
Segmentation of line, word and character are one of the critical phases of optical character recognition (OCR). Due to the imperfection in segmentation, most of the recognition system produce poor recognition rate. In this paper we are discussing some novel approach for line, word and character segmentation of printed Manipuri document. Few works has been done for optical character recognition on other Indian script however in case of Manipuri language it is almost negligible. To the best of our knowledge this is the first report on segmentation of documents containing Manipuri script forms. So keeping these things in mind here, in this paper we are discussing some approach to succeed in the above mentioned task. Here first we are discussing about the structure of Manipuri language, and then we discuss some idea for segmentation of line, word and character from degraded Manipuri document. Finally we discuss about various existing recognition technique.
Keywords :
document image processing; image segmentation; optical character recognition; Indian script; Manipuri machine printed text; Manipuri script forms; OCR; character segmentation; document segmentation; line segmentation; optical character recognition; printed Manipuri document; word segmentation; Character recognition; Handwriting recognition; Hidden Markov models; Image segmentation; Noise; Optical character recognition software; Support vector machines; Character segmentation; HMM; Histogram; Line-segmentation; SVM; Word segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN :
978-1-4799-6928-9
Type :
conf
DOI :
10.1109/CICN.2014.55
Filename :
7065474
Link To Document :
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