A new corner detection method of gray-level image using Hessian matrix
Hang-Ki Ryu, Jae-Kook Lee, Eoun-Taeg Hwang, Jing Liu, Hong‐Hee Lee, Won-Ho Choi · 2007
This paper proposes a new corner detection method based on the Hessian matrix. The proposed method can detect features of a pattern or input image using eigenvalue and eigenvector of images. The Hessian matrix has information of ellipse with intensity variance, and corner can be detected by using the eigen-value and eigen-vector analysis and decided weight value. In order to evaluate the proposed algorithm, experiments are performed in many type images. As the result of the test image, it shows the better performance than that of conventional Harris, SUSAN, and symmetric corner detectors.