Novel medical image cryptogram technology based on segmentation and DNA encoding

Abstract

This paper proposes a novel medical image cryptogram technology based on a fast and robust fuzzy C-means clustering image segmentation method and deoxyribonucleic acid encoding. In our method, first, the medical image is divided into background areas and regions of interest utilizing fuzzy C-means clustering image segmentation, which increases the encryption efficiency by about 60% when the background area is discarded. Second, some low-value pixels are also discarded in regions of interest to further reduce the encryption time. Third, a 4-dimensional hyperchaotic system has been improved. Furthermore, the hyperchaotic system and deoxyribonucleic acid encoding are utilized to encrypt the medical image. Finally, lossless encryption and fast encryption are done for different purposes. The experimental results demonstrate that the proposed algorithm has appealing encryption performance and the histogram and scatter graphs are governed by approximately uniform distribution. The NPCR and UACI of plaintext sensitivity and the key sensitivity are close to 99.6094% and 33.4635% respectively, which cause robustness against noise and clipping attacks.