Abstract
Fast and robust feature extraction is crucial for many computer vision applications such as image matching. The representative and the state-of-the-art image features include Scale Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), and Affine SIFT (ASIFT). However, neither of them is fully affine invariant and computation efficient at the same time. To overcome this problem, we propose in this paper a fully affine invariant SURF algorithm. The proposed algorithm makes full use of the affine invariant advantage of ASIFT and the efficient merit of SURF while avoids their drawbacks. Experimental results on applications of image matching demonstrate the robustness and efficiency of the proposed algorithm.
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