The Journal of the Acoustical Society of Korea

한국음향학회 (The Acoustical Society of Korea)
권호 표지

Classification of Seabed Physiognomy Based on Side Scan Sonar Images

  • Sun, Ning (Underwater Acoustic Communication Institute, Soongsil University) ;
  • Shim, Tae-Bo (Underwater Acoustic Communication Institute, Soongsil University)
  • 발행 : 2007.12.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

As the exploration of the seabed is extended ever further, automated recognition and classification of sonar images become increasingly important. However, most of the methods ignore the directional information and its effect on the image textures produced. To deal with this problem, we apply 2D Gabor filters to extract the features of sonar images. The filters are designed with constrained parameters to reduce the complexity and to improve the calculation efficiency. Meanwhile, at each orientation, the optimal Gabor filter parameters will be selected with the help of bandwidth parameters based on the Fisher criterion. This method can overcome some disadvantages of the traditional approaches of extracting texture features, and improve the recognition rate effectively.

키워드

참고문헌

  1. Adams, A. Lawlor, M. Riyait, 'A real-time synthetic aperture sonar system,' IEEE, Proceedings on Radar, Sonar and Navigation, 143 (3), 169-176, 1996
  2. P. Cervenka, and C. de Moustier, 'Side-Scan Sonar Image Processing Techniques,' IEEE, Journal of Oceanic Engineering, 108-122, 1993
  3. D. Sylvie and F. L eannec, 'Side-Scan Sonar Image Matching,' IEEE, Journal of Oceanic Engineering, 245-259, 1998
  4. B. Wang and J. Tian, C. Zhang, 'Target Detection in Underwater Acoustic Images,' Journal of Detection & Control, 26 (4), 34-38, 2004
  5. J. Tian and C. Zhang, 'Fractal-based Detection of Objects in Underwater Images,' Journal of Image and Graphics, 479-483, 2005
  6. L. Zhong and X. Tian, D. Zhou, 'Man-made Object Detection Algorithm of Sonar Image Based on Texture Analysis,' Institute of Electronic Engineering, Naval University of Engineering, 2006
  7. A Goman, R. and T. J. Sejnowski, 'Analysis of Hidden Units in a Layered Network to Classify Sonar Targets,' (Neural Networks, 1998, 75-89)
  8. R. P. Lippman, 'An Introduction to Computation with Neural Nets', IEEE ASSP Magazine, 1987
  9. C. Shang and K. Brown, 'Cascaded Neural Networks Based Image Classifier', IEEE Int. Con. On Acoustics, Speech, and Signal Processing, Minnesota, U.S.A. 617-620, 1993
  10. Jiang and M. Stewart, M. Marra, 'Segmentation of Seafloor Sidescan Imagery Using Markov Random Field and Neural Networks', Proceedings of OCEANS, IEEE-OES, 456-461, 1993
  11. R. Haralick, 'Statistical and Textural Approaches to Textures,' Proceedings of the IEEE, 67 (5), 786-804, 1979 https://doi.org/10.1109/PROC.1979.11328
  12. J. M. Bell, M. J. Chantler, 'Side-Scan Sonar: A Directional Filter of Seabed Texture?,' IEE Proc -Radar, Sonar Navig, 146 (1), 118-120, 1999
  13. W. Ying Li and L. Zhuo fu, S. Enfang, 'Sonar Image Classification Based on Directional Wavelet and Fuzzy Fractal Dimension,' Second IEEE Conference on Industrial Electronics and Applications, 118-120, 2007
  14. Sun Nand S. Xu, M. Cao, 'Wall-Pasted Cell Segmentation Based on Gabor Filter with Parameter Constraint,' ICARCV 2006
  15. J.G. Daugman, 'Complete Discrete 2D Gabor Transforms by Neural Networks for Image Analysis and Compression,' IEEE Trans. Acoustics, speech, and Signal Processing, 1169-1179, 1998
  16. S. Theodoridis, and K. Konstantinos, Pattern Recognition(Qinghua University, 2007.1, pp.524-528)