Local invariant descriptor for image matching

Image matching is a fundamental task of many computer vision problems. In this paper we present a novel approach for matching two images in the presence of image rotation, scale, and illumination changes. The proposed approach is based on local invariant features. A two-step process detects local invariant regions. Characteristic circles associated with these regions illustrate the position and radius of the regions. Then, the regions are represented by a new image descriptor. To test the new descriptor, we evaluate it in image matching and retrieval experiments. The experimental results show that using our descriptors results in effective and faster matching.