Abstract: To study personalized demands for kitchen appliance replacements and upgrades, this paper propose an image-processing-based visualization system. By analyzing semantic information and structural features (e.g., line textures) from user-submitted kitchen images, the system identifies spatial relationships between key components (e.g., cabinets) and applies empirical kitchen layout principles to derive optimal appliance placement rules. Even with imprecise user input, it predicts ideal positions for target appliances (e.g., dishwashers, refrigerators, ovens) and simulates virtual installations. The results are visualized as augmented images, significantly enhancing the convenience and realism of DIY kitchen design.

Key words: Partial renovation, Image processing, Semantic segmentation, Line segment detection, Visualization