Image segmentation is a key step of oil spills detection in SAR images. For the problem that the traditional multi-spectral clustering algorithm with the features extraction by GLCM (Gray-Level Co-occurrence Matrix) has such limitations as direction sensitivities and difficulties in selecting the best feature combination etc., this paper proposes a multi-scale segmentation method of oil spills in SAR images based on JSEG and spectral clustering. Multi-scale J-images are used to extract the multi-features and the Laplace matrix is clustered by the K-means method. Finally, a decision-level fusion strategy is used to fuse the segmentation results from different scales. Two sets of experiments show that, compared to the traditional spectral clustering methods based on the gray feature and multi-textual features, the proposed method has higher accuracy and stronger robustness.
목차
Abstract 1. Introduction 2. Method 2.1. Color Quantization and Feature Extraction 2.2. Multi-scale Spectral Clustering Segmentation 2.3. Decision Fusion based on the Voting Mechanism 2.4. Implementation of Proposed Method 3. Analysis of Experimental Results 4. Conclusion Acknowledgements References
Chao Wang [ College of Computer and Information Engineering, Hohai University, Nanjing 211100, P.R. China ]
Li-Zhong Xu [ College of Computer and Information Engineering, Hohai University, Nanjing 211100, P.R. China, Engineering Research Center of Sensing and Computing, Hohai University, Nanjing, 211100, P.R. China ]
Corresponding Author
Xin Wang [ College of Computer and Information Engineering, Hohai University, Nanjing 211100, P.R. China, Engineering Research Center of Sensing and Computing, Hohai University, Nanjing, 211100, P.R. China ]
Feng-Chen Huang [ College of Computer and Information Engineering, Hohai University, Nanjing 211100, P.R. 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.7 No.1