Sidescan sonar segmentation using active contours and level set methods

Maria Lianantonakis, Yvan R. Petillot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Citations (Scopus)


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 side scan image containing two distinct regions. A region based active contour model of Chan and Vese [3] is then applied to the vector valued images extracted from the original data. The set of features considered is the Haralick feature set based on the co-occurence matix. To improve computational efficiency the extraction of the Haralick feature set is implemented by using sum and difference histograms as proposed by Unser [16]. Our implementation includes an 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 initialisation are analysed. ©2005 IEEE.

Original languageEnglish
Title of host publicationOceans 2005 - Europe
Number of pages6
Publication statusPublished - 2005
EventOceans 2005 - Europe - Brest, France
Duration: 20 Jun 200523 Jun 2005


ConferenceOceans 2005 - Europe


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