Digital biometric facial image encryption using chaotic cellular automata for secure image storages

Abstract

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.