An Image Segmentation Method Based on Renyi Relative Entropy and Gaussian Distribution

Abstract

Background: Image segmentation is a necessary prerequisite for many higher level computer vision tasks, such as object recognition, image understanding, and image retrieval. However, the segmentation problem is inherently ill-posed due to the large number of possible partitionings for any single image. So, image segmentation remains one of the major challenges in image analysis. There are also many patents on these problems. This paper introduces a new image segmentation method to readers, and the effectiveness of the new method is demonstrated by experiments. Keywords: Image segmentation, histogram thresholding, Renyi relative entropy, Gaussian distribution, parametric statistical model.