Efficient edge matching using improved hierarchical chamfer matching

Abstract

Matching is a central problem in pattern recognition and computer vision, its applications includes object detection and tracking. HCMA (hierarchical chamfer matching) is a classical image matching algorithm, which utilizes the edge information to match the images robustly and the multi-resolution pyramid to accelerate the matching process. However, for images with cluttered background and high resolution, HCMA is relatively computationally expensive, which has impeded its success in practical applications, especially in real-time applications. In this paper, an improved hierarchical chamfer matching algorithm is proposed to reduce its computational cost without degrading its matching quality. According to the experimental results, the proposed improvements are able to save 75% ~ 95% of the computational time, without causing any false matching.