Narrowband Chan-Vese model of sonar image segmentation: A adaptive ladder initialization approach

Abstract

A narrowband Chan-Vese model with adaptive ladder initialization approach is proposed in this paper to segment underwater sonar image. Specifically, for the first time, the problem of more iterative times, human intervention necessity and lower segmentation accuracy, which are commonly exist in the SDF and BIF, was solved with the method utilizing the new adaptive ladder initialization of zero level set. Then, to further reduce the impact of the global search on traditional Chan-Vese model, the narrowband Chan-Vese model is introduced. It is shown that by applying the adaptive ladder initialization is ultimately local optimization and accurate segmentation results. On this basis, recurring to analysis of traditional Chan-Vese model law, combined with narrowband Chan-Vese model with adaptive ladder initialization approach, the objective and quantitative analysis method is developed. Finally, segmentation results demonstrate the effectiveness and adaptability of the proposed method.