Perceptual image hashing is an emerging solution for multimedia content authentication. Due to most perceptual image hashing techniques focus on the robustness but ignore their sensitivity to trivial tampering area, such techniques might not work well when malicious attack is perceptually insignificant. Through experiments we found that some state-of-the-art image hash algorithms could not distinguish small malicious distortion and some authentic distortion. So we propose a novel method about detection of trivial image tampering via unmatched feature points clustering in this paper. First, we extract SURF (Speeded Up Robust Features) feature points but do not use its original descriptor, we...