Salient region detection using fusion of image contrast and boundary information

Abstract

Finding most striking region in an image is known as salient region detection. This area is becoming an area of research in recent years due to its wide applicability in computer vision, robotics and data transmission. To find salient region various parameters like color, texture, location, semantics etc are used. In this paper, a method is proposed which uses the fact that image boundary is rarely touched by salient object and then poisson distribution is used to find the probability of each pixel being part of salient object. Thus, the saliency map is obtained by computing the absolute difference of pixel intensity with the mean of boundary pixels. No former training is essential for this approach. Experiments are performed to evaluate the performance of proposed approach on MSRA dataset and compared with 4 recent state-of-arts. Precision, recall and F-measure proves the consistency of proposed work.