An improved SUSAN corner detection algorithm based on adaptive threshold

The SUSAN operator needs to adjust similarity threshold manually time after time in order to achieve a good corner detection results, and it can´t detect some corners with special or complex shape. In view of this, the SUSAN operator is improved by the authors of this paper. Firstly, an adaptive threshold selection method based on iterative operation is proposed, and then a discrete ring-shaped mask is added within the SUSAN´s circular mask so as to overcome the deficiency of the SUSAN operator. The experimental results show that the improved SUSAN algorithm can not only greatly improve the automation of program operation by releasing the programmers of adjusting threshold manually, but also obtain a good detection result for various types of corners.