Journal of Information Organization Shiqing Chen 15 4 2025 https://doi.org/10.6025/jio/2025/15/4/171-178 https://www.dline.info/jio/fulltext/v15n4/jiov15n4_2.pdf The paper presents an innovative design system for traditional embroidery patterns using a linear classifiertype intelligent algorithm model in computer science. Recognizing the limitations of conventional, artisandependent embroidery design such as constrained creativity and pattern diversity the study proposes an AIdriven approach to automate and enhance pattern innovation while preserving cultural essence. The system involves preprocessing embroidery images, extracting geometric, textural, and structural features, and applying linear classifiers like Support Vector Machines and Logistic Regression to categorize and generate new designs. A user friendly visual interface allows customization, fostering personalized creativity. Experimental validation includes dataset partitioning, algorithm comparison, and performance evaluation using metrics like accuracy, recall, and F1 score. Results indicate that the linear classifier effectively identifies pattern features and supports the generation of innovative designs. The research fills a gap in intelligent systems explicitly tailored for embroidery, as most prior work focused on digital art or painting. By integrating machine learning with traditional craftsmanship, the system not only modernizes embroidery design but also contributes to the preservation and evolution of cultural heritage. The authors suggest exploring alternative algorithms to refine performance further and broaden the application scope. Overall, the study demonstrates the feasibility and practical value of intelligent algorithms in revitalizing traditional art forms through computational innovation.The Innovation Design System for Traditional Embroidery Patterns Based on the Linear Classifier type Intelligent Algorithm Model in Computer