Saliency detection via background prior and foreground seeds

Abstract

As an image pre-processing technology, saliency detection (DS) can be used in a wide variety of visual tasks. A bottom-up method of DS via background prior and foreground seeds is proposed. To highlight the object and suppress the background noise, two saliency maps are obtained by using the background prior and foreground seeds. First, we use global colour and spatial distance matrices to compute a background saliency map. To evenly emphasize the saliency region, the single-layer cellular automata is used to refine the background-based saliency map. Second, a set of foreground seeds is obtained from the refined background-based saliency map. Then, the foreground-based saliency map is calculated based on the foreground seeds and refined by biased Gaussian filtering. The proposed method could emphasize the foreground target, as well as restrain the background noise. The experiment results show that our method has good ability in saliency detection.