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http://dx.doi.org/10.6109/jkiice.2014.18.6.1269

ART2 Based Fuzzy Binarization Method with Low Information Loss  

Kim, Kwang-Baek (Department of Computer Engineering, Silla University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.6, 2014 , pp. 1269-1274 More about this Journal
Abstract
In computer vision research, binarization procedure is one of the most frequently used tools to discriminate target objects from background in grey level binary image. Fuzzy binarization is a reliable technique in environment with high uncertainty such as medical image analysis by setting the threshold as the average of minimum and maximum brightness with triangle type fuzzy membership function. However, this technique is also known as contrast sensitive method thus its discrimination power is not so great when the image has low contrast difference between objects and backgrounds and suffer from information loss as a result. Thus, in this paper, we propose a fuzzy binarization using ART2 algorithm to handle such low contrast image analysis. Proposed ART2 algorithm is applied to determine the medium point of membership function in the fuzzy binarization paradigm. The proposed methods shows low information loss rate in our experiment.
Keywords
Threshold; Membership function; ART2; Fuzzy binarization;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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