Texture segmentation via a diffusion-segmentation scheme in the Gabor feature space
Chen Sagiv, Nir Sochen, Yehoshua Y. Josh Zeevi · 2004
We address the problem of texture segmentation in the context of the Gabor feature space of images. Gabor filters which are tuned to different orientations, scales and frequencies are applied to textured images to create the Gabor feature space. We regard the scale, orientation and frequency for which maximum response of the Gabor filters was obtained. A two-dimensional Riemannian manifold of local features is extracted via the Beltrami framework. The metric of this surface is a good indicator of texture changes and is used, therefore, in a Beltrami based diffusion mechanism and in a geodesic active contours algorithm for texture segmentation. The innovation of this work lies in using the metric of the feature manifold which integrates information from all the features, in both the diffusion and segmentation processes.