Digital biometric facial image encryption using chaotic cellular automata for secure image storages
S. Cheepchol, Wimol San-Um, Supaporn Kiattisin, Adisorn Leelasantitham · 2014
This paper presents the digital image encryption scheme for biometric facial image using Cellular Automata (CA) for secure image storage. The proposed scheme is relatively simple using a segmentation of CA binary image with embedded secret keys generated by the third class of well-known Wolfram Cellular Automata that exhibits chaotic patterns. Such segmented CA binary image is diffused to the shuffled and bit-plane separated of the original biometric facial image through to XOR operations. Experiments have been performed in MATLAB using a standard digital biometric facial image with the size of 160×160 pixels. Encryption qualitative performances are evaluated through pixel density histograms, 2-dimensional power spectral density, and vertical, horizontal, and diagonal correlation plots. For the encryption quantitative measures, correlation coefficients, entropy, NPCR and UACI are realized. Demonstrations of wrong-key decrypted image are also included. The proposed encryption scheme offers a potential alternative to digital biometric facial image storage in a various applications such as in border security control, payment system, or in crime prevention, detection, and forensics.