Attention region detection based on closure prior in layered bit Planes

An attention region usually possesses a closed contour and a significant color contrast against its surroundings. Inspired by this observation, a novel prior so called closure prior is introduced as an important high-level saliency cue in this paper. Specifically, firstly, the connectivity analysis is used in layered bit planes to extract closed regions based on closure prior. Secondly, the closed regions touching image boundaries are removed based on the assumption that most photographers will not crop attention regions along the view frame. Thirdly, based on the hypothesis that an image region should have a big contrast against its surroundings if it has more chances in all bit planes to be a closed region, the contrast contributions of a closed region in all bit planes are accumulated to obtain color contrast. Meanwhile, by taking account for the characteristics of human visual system according to the perception of small attention region, and the mechanism of human visual resource allocation between attention regions, several morphological filtering technologies are applied to the steps of color contrast calculating. Finally, the saliency map aiming for attention region detection is generated from the contrast map. The experimental results show the presented detection method achieves acceptable performance compared with twelve state-of-the-art models.