Application of Visual Communication Technology in Image Enhancement and Optimization of Human Machine Interaction Interface

To address the technical issues in the design process of traditional human-computer interaction systems, a human-computer interaction system design based on visual communication technology is implemented. Firstly, for the skin color detection method in color space, a neural network color filter based on fuzzy patterns is created based on the BP neural network model based on the threshold changes of different lighting conditions. The filter designed in this paper has a fast learning speed and can be used in vast lighting conditions and complex environments. Moreover, the human-computer interaction system has been meticulously crafted to align seamlessly with users' accustomed practices. Leveraging the EC5-1719CLDNA embedded star as its hardware foundation, the system integrates a compact projection unit and a radiation control system. On the software front, a paperless office interaction engine has been developed, making optimal use of the robust computational capabilities offered by multithreading and the selected hardware platform. Subsequently, rigorous testing was conducted, affirming that the system not only meets but surpasses the specified operational demands.