Intelligent Machine Learning in Image Authentication

Image authentication techniques have recently gained great attention due to its importance for a large number of multimedia applications. Digital images are increasingly transmitted over non-secure channels such as the Internet. Therefore, military, medical and quality control images must be protected against attempts to manipulate them; such manipulations could tamper the decisions based on these im- ages. To protect the authenticity of multimedia images, there are several approaches including conventional cryptography, fragile and semi-fragile watermarking and dig- ital signatures that are based on the image content. The aim of this paper is to present a review on different Machine learning techniques as Fuzzy Set Theory, Rough Set Theory, Rough K-means clustering, Near Sets and Nearness Approximation Spaces, Vector quantization, Genetic Algorithm, Particle Swarm Optimization, Support Vec- tor Machine and applying them in image authentication.