Sidescan Sonar Segmentation Using Texture Descriptors and Active Contours

Abstract

This paper is concerned with the application of active contour methods to unsupervised binary segmentation of high-resolution sonar images. First, texture features are extracted from a sidescan image containing two distinct regions. A region-based active contour model of Chan et al. [J. Vis. Commun. Image represent, vol. 11, pp. 130-141,2000] is then applied to the vector-valued image extracted from the original data. Our implementation includes a new automatic feature selection step used to readjust the weights attached to each feature in the curve evolution equation that drives the segmentation. Results are shown on simulated and real data. The influence of the algorithm parameters and contour initialization are also analyzed.

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