Restaurant Interior Design under Digital Image Processing Based on Visual Sensing Technology

With the development of the social economy, people are paying more and more attention to decorative effects and the comfort and individual characteristics of decoration. To meet the increasingly high requirements of customers, many restaurants have begun to focus on the personalization of the dining environment, which is comfortable to build and focuses on the spiritual satisfaction and experience of customers during the dining process. In this study, a comprehensive analysis of digital image processing technology is performed to implement an automatic illumination system with improved performance for the restaurant interior design and embed the restaurant interior design with intelligence. The convolutional neural network (CNN) is employed in the automatic illumination system to develop the human body recognition model. After a test of its recognition accuracy, the parameters of CNN are optimized, and high recognition accuracy of 0.97 is achieved. Compared with other models, the process of training the designed model implemented in this study can finish in 40 minutes, and the performance has been well optimized. Moreover, the processing function of the model is also able to resist the interference of other external objects. The excellent automatic illuminating system can greatly improve the atmosphere as well as the service level of the restaurant at night, which can promote the modernization of the restaurant and give certain reference significance to the reform and advancement of the decoration industry.