Image salient regions encryption for generating visually meaningful ciphertext image

被引:45
|
作者
Wen, Wenying [1 ]
Zhang, Yushu [2 ,3 ]
Fang, Yuming [1 ]
Fang, Zhijun [4 ]
机构
[1] Jiangxi Univ Finance & Econ, Sch Informat Technol, Nanchang 330013, Jiangxi, Peoples R China
[2] Southwest Univ, Sch Elect & Informat Engn, Chongqing 400715, Peoples R China
[3] Shenzhen Univ, Coll Comp Sci & Engn, Shenzhen 518060, Peoples R China
[4] Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai 201620, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2018年 / 29卷 / 03期
基金
中国国家自然科学基金;
关键词
Saliency detection; Feature encryption; Visually meaningful ciphertext image; CHAOTIC SYSTEM;
D O I
10.1007/s00521-016-2490-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image feature encryption is comprised of feature extraction and feature encryption. The existing feature encryption algorithms aim at extracting edge features as significant information for encryption purpose rather than salient regions. However, salient regions in the images usually carry more important information than edge features. Moreover, most of them protect significant information by transforming the input image into noise-like image or texture-like image. Obviously, these images are sign of encrypted image and thus can be easily attacked. In this study, we propose a salient regions encryption method by generating visually meaningful ciphertext image. First, salient regions are efficiently detected by saliency detection model in the compressed domain. Then, we encrypt these salient regions by a chaos-based encryption algorithm. With optical encryption theory, the encrypted salient regions are finally transformed into a visually meaningful ciphertext. To the best of our knowledge, it is the first time to use salient regions as important visual information for encryption to obtain ciphertext image. Results demonstrate the image salient regions have been largely hidden with the proposed method.
引用
收藏
页码:653 / 663
页数:11
相关论文
共 50 条
  • [1] Image salient regions encryption for generating visually meaningful ciphertext image
    Wenying Wen
    Yushu Zhang
    Yuming Fang
    Zhijun Fang
    [J]. Neural Computing and Applications, 2018, 29 : 653 - 663
  • [2] Image encryption: Generating visually meaningful encrypted images
    Bao, Long
    Zhou, Yicong
    [J]. INFORMATION SCIENCES, 2015, 324 : 197 - 207
  • [3] Visually Meaningful Image Encryption
    Arunkumar, S.
    Senthilselvan, N.
    Jangiti, Saikishor
    [J]. RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES, 2016, 7 (06): : 128 - 135
  • [4] Image Cryptosystem for Visually Meaningful Encryption Based on Fractal Graph Generating
    Bai, Sen
    Zhou, Longfu
    Yan, Mingzhu
    Ji, Xiaoyong
    Tao, Xuejiao
    [J]. IETE TECHNICAL REVIEW, 2021, 38 (01) : 130 - 141
  • [5] A Meaningful Visually Secure Image Encryption Scheme
    Fu, Jie
    Ping, Ping
    Gao, Zeyu
    Mao, Yingchi
    [J]. 2019 IEEE FIFTH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING SERVICE AND APPLICATIONS (IEEE BIGDATASERVICE 2019), 2019, : 199 - 204
  • [6] Hierarchical identification of visually salient image regions
    Li, Qian
    Wang, Shuozhong
    Zhang, Xinpeng
    [J]. 2008 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2008, : 1708 - 1712
  • [7] Visually Meaningful Multi-image Encryption Scheme
    Laiphrakpam Dolendro Singh
    Khumanthem Manglem Singh
    [J]. Arabian Journal for Science and Engineering, 2018, 43 : 7397 - 7407
  • [8] Primitively visually meaningful image encryption: A new paradigm
    Zhao, Ruoyu
    Zhang, Yushu
    Nan, Yu
    Wen, Wenying
    Chai, Xiuli
    Lan, Rushi
    [J]. INFORMATION SCIENCES, 2022, 613 : 628 - 648
  • [9] Visually Meaningful Multi-image Encryption Scheme
    Singh, Laiphrakpam Dolendro
    Singh, Khumanthem Manglem
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (12) : 7397 - 7407
  • [10] Systematic Survey on Visually Meaningful Image Encryption Techniques
    Himthani, Varsha
    Dhaka, Vijaypal Singh
    Kaur, Manjit
    Singh, Dilbag
    Lee, Heung-No
    [J]. IEEE ACCESS, 2022, 10 : 98360 - 98373