- 크기와 회전변화에 강인한 Genetic Programming 기반 코너 검출자
- ㆍ 저자명
- 서기성,김영균,Seo. Ki-Sung,Kim. Young-Kyun
- ㆍ 간행물명
- 제어·로봇·시스템학회 논문지
- ㆍ 권/호정보
- 2010년|16권 4호|pp.339-345 (7 pages)
- ㆍ 발행정보
- 제어로봇시스템학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
This paper introduces GP(Genetic Programming) based robust corner detectors for scaled and rotated images. Various empirical algorithms have been studied to improve computational speed and accuracy including approaches, such as the Harris and SUSAN, FAST corner detectors. These techniques are highly efficient for well-defined corners, but are limited to corner-like edges which are often generated in rotated images. It is very difficult to detect correctly edges which have characteristics similar to corners. In this paper, we have focused the above challenging problem and proposed Genetic Programming-based automated generation of corner detectors which is robust to scaled and rotated images. The proposed method is compared to the existing corner detectors on test images and shows superior results.