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Image identification is one of the most challenging tasks in different areasof computer vision. Scale-invariant feature transform is an algorithm to detectand describe local features in images to further use them as an image matchingcriteria. In this paper, the performance of the SIFT matching algorithm againstvarious image distortions such as rotation, scaling, fisheye and motiondistortion are evaluated and false and true positive rates for a large numberof image pairs are calculated and presented. We also evaluate the distributionof the matched keypoint orientation difference for each image deformation.

Image Identification Using SIFT Algorithm: Performance Analysis against Different Image Deformations