Abstract: Aiming at the problem that the features extracted from the color image by existing copy-move forgery detection (CMFD) algorithms are not comprehensive and the matching time is too high,the blind identification algorithm for digital images by using quantized color features and SURF detector was studied.In the feature extraction process,the algorithm combines HSV fuzzy quantization color feature and SURF feature to form a comprehensive description,called the FCQ-SURF features,of color image content.K-Means clustering and KNN method are used to improve matching efficiency in feature matching stage.The experimental results show that the algorithm can detect and locate the colorima-ge copy-move forgery well in CASIA 1.0 and FAU color image test library.It also has a good detection effect for multiple tampering attacks and multi-region tampering of images.The experimental results demonstrate that the proposed algorithm has higher detection accuracy and better matching time for color image copy-move forgery.

Key words: Blind image identification, Copy-move forgery, FCQ-SURF features, K-Means clustering matching