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Automatic Recognition of Woven Fabric Pattern Based on TILT

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  • Zhitao Xiao
  • Yongmin Guo
  • Lei Geng
  • Jun Wu
  • Fang Zhang
  • Wen Wang
  • Yanbei Liu

Abstract

In this paper, an effective method based on Transform Invariant Low-rank Textures (TILT) and HOG is proposed to identify woven fabric pattern. Firstly, the method based on TILT is used to solve the deflection phenomenon in the process of woven fabric image acquisition. Secondly, the yarn floats in the fabric image is localized by the yarns segmentation method based on the 2D spatial-domain gray projection, which is used to segment the weft and warp yarns. Thirdly, HOG is applied to extract distinctive invariant features in the process of feature extraction. According to the HOG feature, the texture features of the woven fabric are acquired. Finally, the yarn floats are classified by Fuzzy C-Means (FCM) clustering to recognize the weft and warp cross. Experimental results demonstrate that the proposed method can achieve the recognition of the three woven fabrics, plain, twill, and satin, and obtain accurate classification results.

Suggested Citation

  • Zhitao Xiao & Yongmin Guo & Lei Geng & Jun Wu & Fang Zhang & Wen Wang & Yanbei Liu, 2018. "Automatic Recognition of Woven Fabric Pattern Based on TILT," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-12, September.
    • Handle: RePEc:hin:jnlmpe:9707104
    DOI: 10.1155/2018/9707104
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