Sonar Image Segmentation based on an Improved Level Set Method

Abstract Aiming at the problem that the existing image segmentation methods cannot be accurately applied in sonar image segmentation, an improved level set sonar image segmentation method was proposed in this paper. Firstly, this paper analyzed the different characteristics of sonar image from the optical image, and the biggest drawback among them is the existence of shadow interference, namely for a sonar image with shadow part, the traditional level set segmentation algorithm will often make the shadow as the segmentation target to be exported out because the feature of sonar target object is not significant enough; Secondly, to overcome the shadow negative effects in sonar image segmentation and achieve selective segmentation, this paper did sonar image preprocessing by morphological top-hat and bottom-hat transformation, then carried on level set method without re-initialization and constructed an improved level set sonar image segmentation system; finally, compared the improved level set method with the traditional level set method in the simulation experiment, and the results showed that the improved level set segmentation method is more adapted to sonar image with uneven background.

[1]  Sang-in Park,et al.  Optimal Topology Design of Magnetic Devices Using Level-Set Method , 2009, IEEE Transactions on Magnetics.

[2]  Peter Lonsdale,et al.  Simultaneous operation of the Sea Beam multibeam echo-sounder and the SeaMARC II bathymetric sidescan sonar system , 1990 .

[3]  Shi Hong,et al.  Spectral clustering for sonar image segmentation using morphological wavelet and gray level transformation , 2010, 2010 5th International Conference on Computer Science & Education.

[4]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

[5]  Chunming Li,et al.  Level set evolution without re-initialization: a new variational formulation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[6]  Ning Li,et al.  Image Segmentation Algorithm using Watershed Transform and Level Set Method , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[7]  Enfang Sang,et al.  Sonar image segmentation using snake models based on cellular neural network , 2005, 2005 IEEE International Conference on Information Acquisition.

[8]  J Iang Estimate and Eliminate Background of Image with Top-hat Transformation , 2008 .

[9]  Hernsoo Hahn,et al.  Sonar Image Segmentation Based on Markov Gauss-Rayleigh Mixture Model , 2008, 2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing.

[10]  Chunming Li,et al.  Implicit Active Contours Driven by Local Binary Fitting Energy , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.