Regions of interest extraction based on HSV color space

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Abstract

In this paper, a simple method to extract regions of interest (ROI) from images is proposed. In the field of image processing, intensity, color and orientation are commonly used features for saliency map generation in most visual attention model. However, texture feature can contribute to the guidance of attention in a bottom-up model. We consider texture contrast as a component of final saliency map. Hue, saturation, and value (HSV) color space is also adopted in this paper for its good capability of representing the colors of human perception and simplicity of computation. Moreover, binocular stereo image pair is adopted as source image. The result shows that the proposed saliency computational method can effectively detect salient region, and it is more suitable for environmental perception and cognition, object detection, and mobile robot navigation.

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