Visual Based Contour Detection by Using the Improved Short Path Finding

Abstract

Contour detection is an important characteristic of human vision perception. Humans can easily find the objects contour in a complex visual scene; however, traditional computer vision cannot do well. This paper primarily concerned with how to track the objects contour using a human-like vision. In this article, we propose a biologically motivated computational model to track and detect the objects contour. Even the previous research has proposed some models by using the Dijkstra algorithm [1], our work is to mimic the human eye movement and imitate saccades in our humans. We use natural images with associated ground truth contour maps to assess the performance of the proposed operator regarding the detection of contours while suppressing texture edges. The results show that our method enhances contour detection in cluttered visual scenes more effectively than classical edge detectors proposed by other methods.