Regions of interest extraction from color image based on visual saliency

Many computer vision applications, such as object recognition and content-based image retrieval could function more reliably and effectively if regions of interest were isolated from their background. A new method for regions of interest extraction from color image based on visual saliency in HSV color space is proposed in this paper. Color saliency is calculated by a two-dimensional sigmoid function using the saturation component and brightness component, and we can identify regions with vivid color. Discrete Moment Transform (DMT)-based saliency can determine large areas of interest. A visual saliency map is obtained by combining color saliency and DMT-based saliency, which is denoted the S image. A criterion for the local homogeneity called the E image is calculated in the image. Based on S image and E image, the high visual saliency object seed points set and low visual saliency object seed points set are determined. The seeded regions growing and merging are used to extract regions of interest. Experimental results demonstrate the effectiveness and efficiency of the method for the natural color images.

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