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A Multi-thresholding Approach Improved with Otsu's Method  

Li Zhe-Xue (Dept. of Computer Engineering, Myongji University)
Kim Sang-Woon (Dept. of Computer Engineering, Myongji University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.43, no.5, 2006 , pp. 29-37 More about this Journal
Abstract
Thresholding is a fundamental approach to segmentation that utilizes a significant degree of pixel popularity or intensity. Otsu's thresholding employed the normalized histogram as a discrete probability density function. Also it utilized a criterion that minimizes the between-class variance of pixel intensity to choose a threshold value for segmentation. However, the Otsu's method has a disadvantage of repeatedly searching optimal thresholds for the entire range. In this paper, a simple but fast multi-level thresholding approach is proposed by means of extending the Otsu's method. Rather than invoke the Otsu's method for the entire gray range, we advocate that the gray-level range of an image be first divided into smaller sub-ranges, and that the multi-level thresholds be achieved by iteratively invoking this dividing process. Initially, in the proposed method, the gray range of the object image is divided into 2 classes with a threshold value. Here, the threshold value for segmentation is selected by invoking the Otsu's method for the entire range. Following this, the two classes are divided into 4 classes again by applying the Otsu's method to each of the divided sub-ranges. This process is repeatedly performed until the required number of thresholds is obtained. Our experimental results for three benchmark images and fifty faces show a possibility that the proposed method could be used efficiently for pattern matching and face recognition.
Keywords
영상 분할;스레쉬홀딩;Otsu의 스레쉬흘딩법;패턴 매칭;얼굴 인식;
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Times Cited By KSCI : 1  (Citation Analysis)
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