A NOVEL SEGMENTATION METHOD BASED ON GRAYSCALE WAVE FOR UNDERWATER IMAGES

Mingzhong Yan, Bingyi Huang, Daqi Zhu, and Simon X. Yang

References

  1. [1] A. Taneja, P. Ranjan, and A. Ujjlayan, A performance study of image segmentation techniques, The 4th International Conf. Reliability, Infocom Technologies and Optimization (Trends and Future Directions), Noida, India, 2015, 1–6.
  2. [2] X.D. Li, C.M. Luo, D. Jean, and Y.Z. Tang, Generic object recognition based on feature fusion in robot perception, International Journal of Robotics & Automation, 31(5), 2016, 409–415.
  3. [3] D.J. Jiang, S.C. Wang, Y. Zeng, T. Sun, et al., Agricultural robot visual de-hazing method based on image segmentation map, Transactions of the Chinese Society for Agricultural Machinery, 47(11), 2016, 25–31.
  4. [4] X.F. Bai and W.J. Wang, Principal pixel analysis and SVM for automatic image segmentation, Neural Computing and Applications, 27(1), 2016, 45–58.
  5. [5] M. Cerman, I. Janusch, R. Gonzalez-Diaz, and G.W. Kropatsch, Topology-based image segmentation using LBP pyramids, Machine Vision and Applications, 27(8), 2016, 1161–1174.
  6. [6] D. Semani, M. Chambah, and P. Courtellemont, Processing of underwater color images applied to live aquarium videos, International Journal of Robotics & Automation, 20(2), 2005, 123–130.
  7. [7] M. Lu, J. Li, R. Li, F. Liu, et al., Underwater image enhancement method using weighted guided trigonometric filtering and artificial light, Journal of Visual Communication and Image Representation, 38, 2016, 504–516.
  8. [8] J.C. Acharya, S.A. Gadhiya, and K.S. Raviya, Objective assessment of different segmentation algorithm for underwater images, The Fourth International Conf Computing, Communications and Networking Technologies, Nassau, Bahamas, 2013, 1–7.
  9. [9] M. Zhang, S. Li, and X. Li, Research on technologies of underwater feature extraction and target location based on binocular vision, The 27th Chinese Control and Decision Conf., Qingdao, China, 2015, 5778–5784.
  10. [10] Y. Chen and Q. Qin, Applications of dynamic adaptive bee colony algorithm in multi-threshold image segmentation, Computer Modelling and New Technologies, 18(11), 2014, 290–295.
  11. [11] J. Zheng, H. Zhang, D. Huang, X. Sun, et al., Adaptive windowed range-constrained Otsu method using local information, Journal of Electronic Imaging, 25(1), 2016, 1–13.
  12. [12] Y. He, B. Zheng, Y. Ding, and H. Yang, Underwater image edge detection based on K-means algorithm, Proc. IEEE Conf. on Oceans, St. John’s, NL, 2014, 1–4.
  13. [13] A.V. Gavand, P. Lokhande, S. Daware, and U. Kulkarni, Image segmentation for nature images using K-mean and fuzzy C-mean, IJCA Proc. International Conf. Recent Trends in Information Technology and Computer Science (ICRTITCS2011), Huangshi, China, 2012, 37–40.
  14. [14] G. Tao, M.R. Azimi-sadjadi, and A. Nevis, Underwater target identification using GVF snake and Zernike moments, Proc. IEEE Conf. on Oceans, Biloxi, MI, 2002, 1535–1541.

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