| Summary: | Aiming to improve the precision and security, and reduce complexity of the encrypted image retrieval algorithm, a scene understanding-based encrypted image retrieval algorithm is proposed in this paper, which encrypts images by chaotic system-based image encryption algorithm, extracts image features-based on two-dimensional multi-scale hidden Markov model, and classifies the indoor scene to establish an offline database. In the online stage, the query image captured by the smart device is first encrypted, and the multi-scale feature extraction and the image scene matching are performed. Then images in the scene are matched one by one using manifold ranking. Finally, the optimal encrypted matching image is obtained by the homography-based image matching algorithm, and the plaintext image is also obtained by the decryption algorithm. Performance analysis and simulation results show that the proposed algorithm can improve the precision of image retrieval and protect the security of users’ privacy.
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