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
相关论文
共 50 条
  • [41] Ensemble of extreme learning machine for remote sensing image classification
    Han, Min
    Liu, Ben
    [J]. NEUROCOMPUTING, 2015, 149 : 65 - 70
  • [42] Remote Sensing Image Classification Based on Ensemble Extreme Learning Machine With Stacked Autoencoder
    Lv, Fei
    Han, Min
    Qiu, Tie
    [J]. IEEE ACCESS, 2017, 5 : 9021 - 9031
  • [43] Remote Sensing Image Classification Algorithm Based on Texture Feature and Extreme Learning Machine
    Liu, Xiangchun
    Yu, Jing
    Song, Wei
    Zhang, Xinping
    Zhao, Lizhi
    Wang, Antai
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 65 (02): : 1385 - 1395
  • [44] Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine
    Chen, Chen
    Li, Wei
    Su, Hongjun
    Liu, Kui
    [J]. REMOTE SENSING, 2014, 6 (06) : 5795 - 5814
  • [45] Hyperspectral image classification using FPCA-based kernel extreme learning machine
    Wei, Yantao
    Xiao, Guangrun
    Deng, He
    Chen, Hong
    Tong, Mingwen
    Zhao, Gang
    Liu, Qingtang
    [J]. OPTIK, 2015, 126 (23): : 3942 - 3948
  • [46] Kernel-based extreme learning machine for remote-sensing image classification
    Pal, Mahesh
    Maxwell, Aaron E.
    Warner, Timothy A.
    [J]. REMOTE SENSING LETTERS, 2013, 4 (09) : 853 - 862
  • [47] Extreme Learning Machine for Multilayer Perceptron
    Tang, Jiexiong
    Deng, Chenwei
    Huang, Guang-Bin
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (04) : 809 - 821
  • [48] Multilayer denoising extreme learning machine
    多层去噪极限学习机
    [J]. 1600, Editorial Board of Jilin University (50):
  • [49] Football Event Classification Using Convolutional Autoencoder and Multilayer Extreme Learning Machine
    Hashmi, Mohammad Farukh
    Bellare, Tejas Bhat
    Suresh, Ankith
    Naik, Banoth Thulasya
    [J]. IEEE SENSORS LETTERS, 2022, 6 (10)
  • [50] Study on suitability and importance of multilayer extreme learning machine for classification of text data
    Rajendra Kumar Roul
    Shubham Rohan Asthana
    Gaurav Kumar
    [J]. Soft Computing, 2017, 21 : 4239 - 4256