N
Ning Wang
Researcher at Harbin Institute of Technology
Publications - 22
Citations - 654
Ning Wang is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Encryption & Chaotic. The author has an hindex of 11, co-authored 22 publications receiving 513 citations. Previous affiliations of Ning Wang include China Aerospace Science and Industry Corporation.
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Journal ArticleDOI
A new approach to chaotic image encryption based on quantum chaotic system, exploiting color spaces
TL;DR: A new color image encryption scheme based on quantum chaotic system that can be characterized by sensitive dependence to initial conditions/parameters is proposed and brilliant characteristics of the proposed scheme are enough security and good performance.
Proceedings ArticleDOI
Finger-vein Verification Using Gabor Filter and SIFT Feature Matching
TL;DR: A novel method to verify the infrared finger-vein patterns is proposed for biometric purposes and the experiment results show that EER is low to 0.46%, which demonstrates the proposed approach is valid and effective for finger-vesin verification.
Journal ArticleDOI
Digital Image Encryption Scheme Based on Multiple Chaotic Systems
Ahmed A. Abd El-Latif,Ahmed A. Abd El-Latif,Li Li,Tiejun Zhang,Ning Wang,Xianhua Song,Xiamu Niu +6 more
TL;DR: The proposed algorithm possesses robust security features such as fairly uniform distribution, high sensitivity to both keys and plainimages, almost ideal entropy, and the ability to highly de-correlate adjacent pixels in the cipherimages.
Journal ArticleDOI
A new meaningful secret sharing scheme based on random grids, error diffusion and chaotic encryption
Ahmed A. Abd El-Latif,Ahmed A. Abd El-Latif,Xuehu Yan,Li Li,Ning Wang,Ning Wang,Jialiang Peng,Jialiang Peng,Xiamu Niu +8 more
TL;DR: A novel secret image sharing scheme that combines random grids, error diffusion and chaotic permutation to encode a secret binary image into meaningful shadow images and shows the effectiveness of the proposed scheme.
Journal ArticleDOI
Toward accurate localization and high recognition performance for noisy iris images
TL;DR: An accurate iris localization and high recognition performance approach for noisy iris images is presented and the thorough experimental results on the challenging iris image database CASIA-Iris-Thousand achieve an EER of 1.8272 %, which outperforms the state-of-the-art methods.