Abstract: Smallest univalue segment assimilating nucleus (SUSAN) is one of the most excellent methods which are robust to noise and less affected by rotation. However, it could not detect all the true corners and generate some false corners in some special case. To solve these problems, an improved SUSAN corner detector is proposed and its performance is compared with SUSAN corner detection. With the improved SUSAN, a corner point is judged based on gray level values of the pixels in a circular neighborhood of the nucleus which is the same as the conventional SUSAN, however, the improved SUSAN calculates the number of the pixels in the univalue adjoining nucleus and connected segment rather than calculate the number of the pixels of univalue nucleus in the neighborhood. Due to this improvement, the improved SUSAN can not only inherit the main merits but also avoid the fatal fault of conventional SUSAN. Experimental results demonstrate that the improved SUSAN corner detection is accurate and efficient.

Key words: corner detection, SUSAN, nucleus