An efficient angle-based shape matching approach towards object recognition

Abstract

The pixel-based contour map is one of the most common used shape representation methods for shape matching in object recognition field. However it is difficult to remain accurate and efficient at the same time when recognizing the objects with diversity of postures or different presence from different perspectives. To solve this problem, in this paper we propose an angle-based shape matching approach by introducing a new concept of angle-based features. Furthermore, the object recognition process adopting such angle-based shape matching approach is described in detail. With numerous experiments conducted on the Weizmann Horse dataset, we demonstrate that the proposed method is accurate, efficient and robust towards different poses and resolutions at the same time.