In this paper, we propose a novel model for unsupervised segmentation of viewer's attention object from natural images based on localizing region-based active contour (LRAC). Firstly, we proposed the saliency detection model via the multi-scale superpixel. Then, object-level shape prior is extracted combining saliency with object boundary information. Finally, this contour is improved by the edge-preserving to generate the initial contour for our automatic object segmentation system. In

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... with localizing region-based active contours that require considerable user interaction, the proposed method does not require it, i.e., the segmentation task is fulfilled in a fully automatic manner. Extensive experiments results on a large variety of natural images demonstrate that our algorithm consistently outperforms the popular existing salient object segmentation methods, yielding higher precision and better recall rates.