Abstract—Segmentation subdivides an image into its constituent regions or objects. Segmentation should stop when the objects of interest have been isolated. In this paper, histogram based segmentation method is proposed. The fuzzy based segmentation algorithm prefers natural images for experimental purpose. Segmentation based on histogram threshold is a method to divide an image containing two regions namely objects and background. Here the optimal threshold can be obtained by finding the similarity between gray levels. Two initial regions should be located at the boundary of histogram, and then by using the index of the fuzziness the optimal threshold point could be found. Object is assigned to dark and the background is assigned to bright. List of modes is a feature that better describes a 1D histogram, a proper segmentation can be obtained by determining appropriate thresholds separating the modes in thehistogram.

Index Terms—fuzzy set theory, fuzzy logic, index of fuzziness, histogram threshold

Cite: K. K. Thanammal, J. S. Jayasudha, R. R. Vijayalakshmi, and S. Arumugaperumal, "Effective Histogram Thresholding Techniques for Natural Images Using Segmentation," Journal of Image and Graphics, Vol. 2, No. 2, pp. 113-116, December 2014. doi: 10.12720/joig.2.2.113-116