Research On Contour Based Shape Matching

In recent decades, computer technology has made great progress, especially the development of Internet technology, this process produces a large number of multimedia information, in which the image information is the most intuitive representation. How to find images we need from a great number of images has become a popular field of research. In the field of computer vision, images have multiple underlying characteristics:color, texture, shape and so on. Shape is a way to describe the characteristics of the image contour. It is the most important information for object recognition. So shape plays a crucial role in the image description and similarity measurement.The study of shape matching includes shape description and similarity measurement. Shape description mainly includes two kind of methods:contour based and region based. Similarity measurement is to calculate the distance between two shapes by a certain criteria, and completes the shape matching. This paper is mainly based on shape contour description methods. Two different kinds of shape descriptors and their similarity measurement methods are carried out. One new method of shape matching is by contour segmentation. Another shape matching method is based on the graph structure.The main content of this paper is as follow:Considering the contour of the shape, this paper uses the discrete curve evolution method to obtain a simplify polygon. According to the vertices of the simplify polygon, two novel methods are proposed:(1) The contour is divided into several fragments, and we extract the maximum curvature value and the direction vector of each segment as the segment descriptor. The whole segment descriptors form a shape descriptor. And then segment distance matrix is calculated, the minimum value of distance matrix is obtained with Hungarian algorithm. Experiments proof that the principle of this method is simple and it is easy to implement. This method has translation and scaling invariance. (2)Delaunay triangulation is used to obtain Delaunay graph for shape contour. We use graph structure to describe the problem of the shape. The same number of sampling points are extracted for each Delaunay graph. According to these sampling points, the minimum circumcircle is constructed to divide the sampling points into several zones. And2-dimension histogram is obtained to describe the shape. Then ground distance matrix is calculated for different zones. After that the improved EMD method is used to obtain distance to complete shape matching. Experiments show that this method can reflect the difference between different types of shape and it has translation, scaling and rotation invariance.