Data Mining-based Optimized Pattern Design and Color Scheme in Planar CAD

As technology progresses and market demand diversifies, there has been an escalation in the expectations pertaining to pattern design and color schemes within computer-aided design (CAD) systems. Through the analysis and research of existing data mining (DM) techniques, this article proposes an improved threshold segmentation method for planar design images. This method can extract key features from images more accurately, providing a foundation for subsequent pattern design and color-matching optimization. In terms of algorithm performance, the algorithm proposed in this article has shown significant advantages in computational efficiency, accuracy, and recall. This method improves the accuracy and robustness of segmentation and makes the segmentation results more in line with human visual perception. Through the display and analysis of experimental results, it can be seen that our method has achieved superior performance in image threshold segmentation tasks. In evaluating graphic design works, users have given good feedback on the works’ aesthetics, functionality, and innovation. These results fully demonstrate the superiority of this method in aesthetic expression, practicality, and creative conception, providing strong evidence for the creative ability and professional level of designers. © 2024, CAD Solutions, LLC. All rights reserved.