计算机与现代化 ›› 2010, Vol. 1 ›› Issue (10): 75-77,8.doi: 10.3969/j.issn.1006-2475.2010.10.019

• 图像处理 • 上一篇    下一篇

SUSAN角点检测算法稳定性改进研究

侯明亮   

  1. 淮海工学院计算机工程学院,江苏 连云港 222005
  • 收稿日期:2010-05-31 修回日期:1900-01-01 出版日期:2010-10-21 发布日期:2010-10-21

Research on Improving Stability of SUSAN Corner Detection Algorithm

HOU Ming-liang   

  1. College of Computer Engineering, Huaihai Institute of Technology, Lianyungang 222005, China
  • Received:2010-05-31 Revised:1900-01-01 Online:2010-10-21 Published:2010-10-21

摘要: SUSAN算法在图像旋转和有噪声的情况下是比较稳定的角点检测方法,但也有漏检和误检的问题。针对其缺陷,提出改进的角点检测方法。改进的办法是将原方法的SUSAN核同值吸收区,替换为在响应圆域内与核像素点灰度值相同,且与核像素点邻接连通的区域。通过改进,避免了原方法漏检和误检的问题,仿真试验结果证明改进方法的正确性和有效性。

关键词: 角点检测, SUSAN,

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

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