关键词: 显著性, SURF, Gist, 图论

Abstract: Because the traditional image segmentation algorithms need the prior information of the object of interest, they usually fail to segment satisfactorily in blind images. In order to obtain the salient regions without prior, this paper proposes a salient image segmentation algorithm based on the human visual attention mechanism. Firstly, the global Gist feature is extracted to collect the correlative image set of the target image. Secondly, the salient region of the target image is computed and extracted in both target image and correlative image set by combining scale invariant feature SURF (speeded up robust features) and Lab color model space feature. Finally, the salient object can be segmented with the assistance of the efficient graph-based image segmentation. The experimental results show that the proposed method is applicable to the blind image which is visual salient semantic.

Key words: saliency, speeded up robust features (SURF), Gist, graph theory