Image matching is a fundamental task of many computer vision problems. In this paper we present a novel approach to match two images in presenting significant geometric deformations and considerable photometric variations. The approach is based on local invariant features. First, local invariant regions are detected by a three-step process which determines the positions, scales and orientations of the regions. Then each region is represented by a novel descriptor. The descriptor is a two-dimensional histogram. Performance evaluations show that this new descriptor generally provides higher distinctiveness and robustness to image deformations. We present the image matching results. The matching results show good performance of our approach for both geometric deformations and photometric variations.
Image matching based on a local invariant descriptor
IEEE International Conference on Image Processing 2005 ; 3 ; III-377
2005-01-01
398929 byte
Conference paper
Electronic Resource
English
Image Matching Based on a Local Invariant Descriptor
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