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http://dx.doi.org/10.9717/kmms.2015.18.7.843

Noise Robust Document Image Binarization using Text Region Detection and Down Sampli  

Jeong, Jinwook (Dept. of Embedded Systems Eng., Incheon National University)
Jun, Kyungkoo (Dept. of Embedded Systems Eng., Incheon National University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.7, 2015 , pp. 843-852 More about this Journal
Abstract
Binarization of document images is a critical pre-processing step required for character recognition. Even though various research efforts have been devoted, the quality of binarization results largely depends on the noise amount and condition of images. We propose a new binarization method that combines Maximally Stable External Region(MSER) with down-sampling. Particularly, we propose to apply different threshold values for character regions, which turns out to be effective in reducing noise. Through a set of experiments on test images, we confirmed that the proposed method was superior to existing methods in reducing noise, while the increase of execution time is limited.
Keywords
Binarization; MSER; Down Sampling; Critical Value; Document Image;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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