Texture-Gradient-Based Contour Detection

In this paper, a new biologically motivated method is proposed to effectively detect perceptually homogenous region boundaries. This method integrates the measure of spatial variations in texture with the intensity gradients. In the first stage, texture representation is calculated using the nondecimated complex wavelet transform. In the second stage, gradient images are computed for each of the texture features, as well as for grey scale intensity. These gradients are efficiently estimated using a new proposed algorithm based on a hypothesis model of the human visual system. After that, combining these gradient images, a region gradient which highlights the region boundaries is obtained. Nonmaximum suppression and then thresholding with hysteresis is used to detect contour map from the region gradients. Natural and textured images with associated ground truth contour maps are used to evaluate the operation of the proposed method. Experimental results demonstrate that the proposed contour detection method presents more effective performance than conventional approaches.