@article{4621,
  author = {Shiqing Chen},
  title = {New algorithms for Embroidery Patterns Using Feature Extraction and Pattern Recognition},
  journal = {Journal of Information Organization},
  year = {2025},
  volume = {15},
  number = {4},
  doi = {https://doi.org/10.6025/jio/2025/15/4/171-178},
  url = {https://www.dline.info/jio/fulltext/v15n4/jiov15n4_2.pdf},
  abstract = {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},
}