Journal
OPTICS AND LASER TECHNOLOGY
Volume 57, Issue -, Pages 236-242Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.optlastec.2013.07.012
Keywords
Information theory; Entropy; Image segmentation
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In many image, video and computer vision systems the image segmentation is an essential part. Significant research has been done in image segmentation and a number of quantitative evaluation methods have already been proposed in the literature. However, often the segmentation evaluation is subjective that means it has been done visually or qualitatively. A segmentation evaluation method based on entropy is proposed in this work which is objective and simple to implement. A weighted self and mutual entropy are proposed to measure the dissimilarity of the pixels among the segmented regions and the similarity within a region. This evaluation technique gives a score that can be used to compare different segmentation algorithms for the same image, or to compare the segmentation results of a given algorithm with different images, or to find the best suited values of the parameters of a segmentation algorithm for a given image. The simulation results show that the proposed method can identify over-segmentation, under-segmentation, and the good segmentation. (C) 2013 Elsevier Ltd. All rights reserved.
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