Automatic separation of machine-printed and hand-written text lines

Author

Pal, U. ; Chaudhuri, B.B.

Author_Institution

Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Calcutta, India

fYear

1999

fDate

20-22 Sep 1999

Firstpage

645

Lastpage

648

Abstract

There are many types of documents where machine-printed and hand-written texts appear intermixed. Since the optical character recognition (OCR) methodologies for machine-printed and hand-written texts are different, it is necessary to separate these two types of text before feeding them to the respective OCR systems. In this paper, we present such a scheme for both Bangla and Devnagari characters. The scheme is based on the structural and statistical features of the machine-printed and hand-written text lines. The classification scheme has an accuracy of about 98.3%

Keywords

character sets; document image processing; image classification; image segmentation; optical character recognition; Bangla characters; Devnagari characters; OCR systems; accuracy; automatic text line separation; classification scheme; handwritten text lines; machine-printed text lines; optical character recognition; statistical features; structural features; Computer vision; Data mining; Handwriting recognition; Histograms; Image segmentation; Natural languages; Neural networks; Optical character recognition software; Pattern recognition; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on

Conference_Location

Bangalore

Print_ISBN

0-7695-0318-7

Type

conf

DOI

10.1109/ICDAR.1999.791870

Filename

791870