In　this　paper,　we　propose　a　novel　face　authentication　approach　based　on　affine　scale　invariant　feature　transform　(ASIFT)　and　structural　similarity　(SSIM).　The　ASIFT　descriptor　defines　key　points　which　are　used　to　match　the　gallery　and　probe　face　images.　The　matched　pairs　of　key　points　are　filtered　based　on　the　location　of　points　in　the　gallery　face　image.　Then　the　similarity　between　sub-images　at　a　preserved　pair　of　matched　points　is　measured　by　Structural　Similarity　(SSIM).　A　mean　SSIM　(MSSIM)　at　all　pairs　of　points　is　computed　for　authentication.　The　proposed　approach　is　tested　on　FERET,　CMU-PIE　and　AR　databases　with　only　one　image　for　enrollment.　Comparative　results　on　the　AR　database　show　that　our　approach　outperforms　state-of-the-art　approaches.　©　2012　Springer-Verlag.