Symmetry Auto-detection Based on Contour and Corner Models

In this paper we present a novel symmetry auto-detection approach which is used for the symmetry detection of the objects in images. Rather than relying on gradients and pixel matching of an image, symmetry can be automatically detected by using corner detection on a symmetry function which is proposed in Hsu´s paper, and a result will be shown to demonstrate the probability that the object in the image is bilateral symmetry. In this paper, we first use modified active contour model to get the contour of the object in an image. Then we use a symmetries evaluation function to get the symmetry function of the contour. Last, we detect corner in the proposed function. By matching corner points, the symmetry function shows us the symmetry-probability of the object. We apply our method in several natural or man-made objects, and they all exhibit significant performance.