Chaotic Encryption Method of Color Image Based on Improved Convolutional Neural Network

Abstract

In order to improve the chaotic encryption ability of color images, a chaotic encryption technology of color images based on improved neural network and chaotic random nonlinear feature mapping is proposed. The multi-pass filter detector is used to collect the feature information of color images, multi-dimensional phase space hierarchical fusion and feature evolution clustering analysis are carried out on the collected color images, the deep chaotic encryption method is used to realize the arithmetic mapping coding processing of color images, the random nonlinear mapping encryption chaotic key control scheduling model of color images is constructed, and the chaotic mapping coding sequence distribution diagram of color image chaotic encryption is established by combining the segmentation prior knowledge of multi-dimensional multi-view images. The shallow feature information and deep feature information of color image are analyzed, and the improved convolutional neural network technology is used to realize information fusion of feature information of each layer, and the chaotic encryption and recognition optimization of color image is realized by using the chaotic map coding sequence distribution map fusion algorithm. Simulation results show that this method has higher accuracy and lower error rate in chaotic encryption of color images, and improves the ability of color image recognition and detection.