In this paper, a new ear anatomy feature edge extraction method based on Hessian matrix is proposed. Stable edge is obtained from principal curvature image across scale space. Firstly, the side face image that includes an ear is filtered and forms Gaussian pyramid. Secondly, the 2D gray image in the pyramid was regarded as a surface, maximum and minimum principal curvature and their direction were calculated by using Hessian matrix, and principal curvature image was formed. The characteristic of surface is that gray level changes in edge area is sharp and the curvature is larger compared to that of the smooth area. In accordance with this characteristic, automatic hysteresis thresholding based on curvature direction flow is used to segment curvature images. Lastly, combine different scale threshold images to get the feature edge image. The experiments demonstrate that extracted feature edge is smooth and connected. New method is robust to noise, and is sensitive to the weak edge, using Hausdorff distance as similarity measurement of two edge images can obtain above 96% recognition rate.
목차
Abstract 1. Introduction 2. Algorithm Description 2.1 The principal Curvature Image Determined by Hessian Matrix 2.2 Automatic Thresholding 3. Experimental Results and Analysis 3.1 Image Sources and pretreatment 3.2 Classification and Recognition 4. Conclusion References
Ma Chi [ School of Computer & Communication Engineering, University of Science and Technology Beijing, Beijing, China, College of Software, University of Science and Technology LiaoNing, Anshan, China, Beihai Yinhe Industry Investment Co.,Ltd., Beihai, China ]
Ban Xiaojuan [ School of Computer & Communication Engineering, University of Science and Technology Beijing, Beijing, China ]
Corresponding Author
Wang Guosheng [ Beihai Yinhe Industry Investment Co.,Ltd., Beihai, China ]
Tian Ying [ College of Software, University of Science and Technology LiaoNing, Anshan, 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.5