Research on the Integration of AI-Based Image Analysis Technology in Product Design Process

This paper introduces the U-Net algorithm for accurate recognition and segmentation of image data. The system can analyze product design sketches and actual finished product images in real time, thereby automatically extracting feature information and providing intelligent assistance for design iteration. In terms of system integration, the study combines deep learning with traditional design tools to build an end-to-end analysis system. The system first designs a model based on the U-Net algorithm, extracts product feature data and generates corresponding three-dimensional models, and then verifies its effect through multiple iterations of simulation tests. The simulation results show that the system has achieved more than 95% accuracy and stability in image analysis, and has strong generalization capabilities for different product types. Data analysis further reveals the significant advantages of the algorithm in shortening the design cycle and improving design accuracy, providing a reliable basis for the practical application of AI technology in product design. This study provides innovative ideas for the system integration of AI image analysis technology and lays the foundation for the intelligentization of future design processes.