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Structural textile pattern recognition and processing based on hypergraphs.

Vuong M Ngo1, Sven Helmer2, Nhien-An Le-Khac3

  • 1Ho Chi Minh City Open University, 35 Ho Hao Hon, Dist. 1, Ho Chi Minh City, Vietnam.

Information Retrieval
|March 24, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for searching textile archives by analyzing weaving patterns. This approach enables efficient retrieval and clustering of complex textile structures.

Keywords:
Clustering and similarityFabricGraph matchingTextile modellingTextile retrievalWeaving

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Area of Science:

  • Digital Humanities
  • Computer Science
  • Textile Science

Background:

  • Digital transformation impacts humanities, necessitating improved access to digitized collections.
  • Current textile archives lack advanced search functionality for intricate weaving patterns.
  • Keyword search and taxonomy-based organization are insufficient for detailed structural analysis.

Purpose of the Study:

  • To develop an approach for recognizing and clustering similar weaving patterns in textile archives.
  • To enhance searchability and accessibility of digitized textile collections.
  • To establish a baseline for retrieval of complex textile structures.

Main Methods:

  • Representing textile structures using hypergraphs.
  • Extracting multisets of k-neighbourhoods to describe weaving patterns.
  • Clustering pattern multisets using various distance measures and algorithms (K-Means, hierarchical agglomerative).

Main Results:

  • The proposed approach demonstrates efficient implementation with linear complexity.
  • Experimental evaluation confirms the quality of querying and clustering large textile datasets.
  • The method successfully models complex and irregular weaving patterns.

Conclusions:

  • This research presents the first practical approach for modeling and retrieving complex weaving patterns.
  • The developed method significantly improves search functionality in digital textile archives.
  • This work establishes a foundational baseline for future research in textile data retrieval.