An object attribute thresholding algorithm for document image binarization

Author

Liu, Ying ; Feinrich, R. ; Srihari, Sargur N.

Author_Institution

Center of Excellence for Document Analysis & Recognition, State Univ. of New York, Buffalo, NY, USA

fYear

1993

fDate

20-22 Oct 1993

Firstpage

278

Lastpage

281

Abstract

Document image binarization is not a completely solved problem for unconstrained document images. Binarization algorithms, whether global or local, can easily fail on images with noisy or complex background, or poor contrast. The authors report preliminary results on a new approach to document image binarization, an algorithm based on gray scale histogram and run-length histogram analysis. Experimental results on unconstrained machine printed address blocks from the US letter mail stream show that over 99% of such address blocks can be correctly binarized

Keywords

document image processing; image segmentation; optical character recognition; US letter mail stream; address blocks; complex background; document image binarization; gray scale histogram; machine printed address blocks; noisy background; object attribute thresholding algorithm; poor contrast; run-length histogram analysis; unconstrained document images; Algorithm design and analysis; Histograms; Image analysis; Image recognition; Image segmentation; Postal services; Shape; Statistics; Streaming media; Text analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on

Conference_Location

Tsukuba Science City

Print_ISBN

0-8186-4960-7

Type

conf

DOI

10.1109/ICDAR.1993.395732

Filename

395732