Image segmentation based on improved OSV decomposition model

Abstract

A new multi-region image segmentation model based on improved OSV image decomposition was proposed for the coexistence of image structure and texture components. The model preserved the divergence-free vector field of texture image, combined multi-region image segmentation model, which made the decomposed texture and structure image more accurate and improved the accuracy of segmentation. In order to solve the proposed model in this paper, the alternating direction multiplier method was designed. The proposed method could accomplish both image decomposition and image segmentation. The experimental results show that compared with the related classical models, the proposed model can significantly improve the subjective visual effect of image segmentation, and the precision, recall and Jaccard similarity coefficient are at least 3.42%, 0.77% and 4.89% higher respectively.

Keywords

• osv decomposition model
• divergence-free vector
• image segmentation
• alternating direction multiplier method
• image decomposition