Encrypted image classification based on multilayer extreme learning machine

被引:26
作者
Wang, Weiru [1 ]
Vong, Chi-Man [1 ]
Yang, Yilong [1 ]
Wong, Pak-Kin [2 ]
机构
[1] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
[2] Univ Macau, Dept Electromech Engn, Macau, Peoples R China
关键词
Encrypted image classification; Privacy preservation; Multi layer extreme learning machine; ELM auto encoder; RECOGNITION; NETWORK;
D O I
10.1007/s11045-016-0408-1
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowadays, numerous corporations (such as Google, Baidu, etc.) require an efficient and effective search algorithm to crawl out the images with queried objects from databases. Moreover, privacy protection is a significant issue such that confidential images must be encrypted in corporations. Nevertheless, decrypting and then classifying millions of encrypted images becomes a heavy burden to computation. In this paper, we proposed an encrypted image classification framework based on multi-layer extreme learning machine that is able to directly classify encrypted images without decryption. Experiments were conducted on popular handwritten digits and letters databases. Results demonstrate that the proposed framework is secure, efficient and accurate for classifying encrypted images.
引用
收藏
页码:851 / 865
页数:15
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