A Study on Edge Board for Blur Image Judgment and Cluster Image Behavior Analysis: AI-Based Image Processing System Research

Abstract

The purpose of this study is to solve the problem that the control center cannot cope with the situation properly due to the difficulty of analyzing the behavior in the case of cluster images or the occurrence of unclear images due to weather conditions and fine dust. Edge board development is necessary for cases in which the image sharpness check and overlap image check are inaccurate. In addition, evaluation techniques such as PSNR (; Peak Signal-to-Noise Ratio) and SSIM (; Structural Similarity Index) are used for the corresponding images to evaluate the degree of image improvement of the model with a validation dataset for each fixed image. After evaluating the model's inference speed in terms of FPS (; Frame Per Second), verification is performed for each stored model for each training, and the improvement rate of the image is calculated to evaluate which model is the most optimal for each weather condition. Development of modular edge board for CCTV (Closed Circuit Television) linked event processing and ICPoIP (Image Check Processing over IP) system for hybrid-based image classification, video improvement solution and superimposed image shape analysis by linking with the video control system Develop solutions for image processing systems to advance the performance of the image processing system.