Fast Corner Detection Using Approximate Form of Second-Order Gaussian Directional Derivative

Abstract

High-efficiency image corner detection, one of the most important and critical basic technology in industrial image processing, is to detect point features from an input image in real-time. In this article, we propose a new corner detection method which has both good performance of corner detection and real-time processing abilities. Firstly, the integral image and the box filter are combined to obtain the second-order derivative response in each direction of the image. Secondly, a new coarse screening mechanism for candidate corners is presented to reduce the complexity of the corner metric. Thirdly, a non-maximum suppression operation is utilized to obtain corners. Finally, the performance evaluation on accuracy of corner detection, localization error, average repeatability, region repeatability, different lighting conditions, and execution time are used to assess the proposed method against twelve state-of-the-art methods. The experimental results show that our proposed detector has good corner detection performance and achieves the requirement of real-time processing.