Image Thresholding by Maximizing the Index of Nonfuzziness of the 2-D Grayscale Histogram

摘要

Image segmentation plays an important role in various image processing appli- cations including robot vision and document image analysis and understanding. In contrast to classical set theory, fuzzy set theory, which takes into account the un- certainty intrinsic to various images, has found great success in the area of image thresholding. In this paper, an image thresholding approach based on the index of nonfuzziness maximization of the 2-D grayscale histogram is proposed. The thresh- old vector (T. S), where T is a threshold for pixel intensity and s is another threshold for the local average of pixels, is obtained by an exhaustive searching algorithm.