Salient object detection irrespective of all textural variations in scene.Eschews all heuristics and computes different weights from the image itself.Assigns a uniform saliency value to all pixels inside the salient region.Extracts the complete contour(s) of salient object(s) from an image.Identifies whether or not an image contains any salient region at all. We propose a texture insensitive, region based image saliency detection algorithm, having excellent detection and localization properties, to obtain salient objects. We use a total variation based regularizer to suppress textures from the image and to make the method invariant to textural variations in the scene. This leads to an image that contains piecewise constant gray valued regions. This texture-free image is sparsely segmented into a small number of regions using the expectation maximization algorithm assuming a Gaussian mixture model. We compute three different saliency measures for every region using its intensity and spatial features. We adopt a relevance feedback mechanism to obtain weights for combining the three saliency measures and obtain the final saliency map. Next we input the thresholded saliency map to an image matting technique and extract the salient objects from the image with exact boundaries. Experimental comparisons with existing saliency detection algorithms demonstrate the superiority of the proposed technique.
['Avik Hati', 'Subhasis Chaudhuri', 'Rajbabu Velmurugan']
An image texture insensitive method for saliency detection