Fuzzy Entropy Based Approach to Image Thresholding
نویسنده
چکیده
Image thresholding plays very important role in many computer vision and image processing applications. Segmentation based on gray level histogram thresholding consists of a method that divides an image into two regions of interest; object and background. In image processing, we deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or uncertainty and provides a new tool to deal with multimodal histograms. In this paper, a novel image thresholding approach is proposed using fuzzy entropy. In the proposed approach, at first the input image is preprocessed to reduce noise without any loss of image details using fuzzy set theoretic approach. Then an optimal threshold is obtained from the preprocessed image using fuzzy entropy. The improvement of the proposed approach is discussed with the help of experimental results on different types of test images. Keywords— Fuzzy entropy, Image segmentation, Noise removal, Thresholding, Uncertainty
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