Visual communication of moving images based on AI recognition and light sensing image edge detection algorithm

With the rapid advancements in information technology and communication technology, the utilization of moving image visual communication has become widespread across various domains. In this context, optical sensing technology plays a pivotal role due to its remarkable attributes including high speed, vast capacity, and minimal delay. Thus, this research aims to enhance the optical sensing effect and edge detection accuracy in moving image visual communication by leveraging AI recognition and an optical sensing image edge detection algorithm. For this purpose, an AI recognition algorithm is implemented to train the model to identify the objects present in the moving images, enabling the localization of target objects within the optical sensing images. Consequently, the edge information of the target object is extracted from the photosensing image by employing an edge detection algorithm. Subsequently, the edge information of the optical sensing image undergoes processing and optimization to enhance the accuracy of edge detection. Through experimental results, it is demonstrated that the proposed approach, which integrates AI recognition and an optical sensor image edge detection algorithm, effectively identifies and localizes target objects within the optical sensor image, consequently improving the accuracy of edge detection outcomes. Furthermore, in comparison to conventional methods, the proposed methodology exhibits superior performance in optical image edge detection.