MATLAB Implementation of Game of Life Scrambling Algorithm

This article presents a MATLAB implementation of the Game of Life scrambling algorithm applied to image encryption. The Game of Life scrambling algorithm is based on cellular automata principles, simulating evolutionary processes within discrete spatial configurations. The implementation utilizes MATLAB's image processing toolkit to transform image appearance and structure through iterative cellular automata rules. Key algorithmic components include neighborhood state evaluation (typically using Moore neighborhood with 8-connected pixels), state transition rules based on birth/survival conditions, and multiple iteration cycles for effective scrambling. The MATLAB code handles image matrix conversion to binary states, applies Conway's Game of Life rules through vectorized operations for efficiency, and reconstructs the scrambled image using logical indexing. Through this implementation, developers can understand cellular automata-based encryption mechanics and apply the algorithm to create unique visual effects in digital image processing projects.