Aiming at the existing edge detection algorithm of edge vague, the pseudo-edge cannot be removed and algorithm results do not achieve optimal results by virtue. In order to improve the reliability and effectiveness of edge detection, the proposed optimization tool template coefficient method, to design the coding, Sobel filter and fitness function of genetic fuzzy clustering algorithm. Through interpolating, smooth handling and filtering with the updated active contour model. Based on the traditional edge detection algorithm is analyzed, combined with fuzzy membership functions and genetic operators for edge detection algorithm was improved by genetic fuzzy clustering. Through the simulation results showed that this new algorithm was feasible. Theoretical analysis and experimental results demonstrate that, the new algorithm in this paper is highly antinoise and able to get better image edges.
목차
Abstract 1. Introduction 2. Genetic Fuzzy Clustering Algorithm 3. Improved Algorithm Based on Genetic Fuzzy Clustering 3.1. The Improved Edge Template 3.2. Coding Design 3.3. Fitness Function Design 3.4. Genetic Operators Design 3.5. Fuzzy Sets and Fuzzy Membership Functions 3.6. Sobel Filter Design 4. Experimental Results and Analysis 5. Conclusion ACKNOWLEDGEMENTS References
Xiaoguang Li [ Department of Electrical Engineering and Automation, Luoyang of Science and Technology, Luoyang, Hennan, 471023, China ]
Corresponding author
Bianxia Wu [ Department of Information Engineering, Luohe Vocational and Technical College, Luohe, Hennan, 462000, China. ]
Yuanbo Li [ School of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China. ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.7