Binocular Image Segmentation Based on Graph Cuts Multi-feature Selection

Binocular image segmentation is crucial for subsequent applications such as stereoscopic object synthesis and 3D reconstruction.Since binocular images contain scene depth information,it is difficult to obtain ideal segmentation results by applying monocular image segmentation methods to binocular images directly.At present,most binocular image segmentation methods use the depth feature of the binocular image as an additional channel for the color feature.Only the color feature and the depth feature are simply integrated,and the depth feature of the image cannot be fully utilized.Based on the multi-class Graph Cuts framework,this paper proposes an interactive binocular image segmentation method.Combining features such as color,depth and texture into a graph model can make full use of different feature information.At the same time,the feature space neighborhood system is introduced in the Graph Cuts framework,which enhances the relationship between the pixels in the foreground and background areas of the image,and improves the integrity of the segmentation target.Experimental results show that the proposed method improves the accuracy of binocular image segmentation results effectively.

Abstract licence: CC BY-NC-ND

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