Multiple visual objects segmentation based on adaptive Otsu and improved DRLSE

Abstract

Aiming at the problem that contours always are fractured and not precise in the segmentation of multiple visual objects, Distance Regularized Level Set Evolution(DRLSE) is used. Considering the characteristics of background difference image, an adaptive Otsu is proposed to segment difference image. In order to take full advantage of temporal information in videos, frame difference and background difference are introduced into energy function of DRLSE. Firstly, an adaptive Otsu and asymmetric morphological filtering based method are used to obtain better initial contours. Secondly, initial contours are evolved with improved DRLSE that frame difference and background difference are integrated in as priori knowledge, which can avoid that objects contours are evolved to background edge, and reduce over segmentation. The experimental results show that the contours of multiple video targets can be obtained more precisely and rapidly with the method proposed in this paper than with the existing methods.