journal article·2025-02-11Open access

Fabric pattern recognition using image processing and AHP method

Manal Al Saleh, Thouraya Hamdi, Mohamed Jmali

AUTEX Research Journal· Volume 25· Issue 1

Abstract

Abstract This article aims to provide methods and a system to recognize the woven fabric patterns automatically. Two different approaches were designed to identify the woven patterns in this article: image analysis and the analytic hierarchy process (AHP). In this work, identifying the woven fabric patterns is based on the measurement of some characteristics and parameters that clearly describe and explain the contexture of the fabric. The methods used were essentially pattern recognition and image processing, which aim to numerically calculate four critical parameters which can give a clear idea of the texture and the patterns of fabrics: the continuity of diagonal lines, the section succession in the vertical direction, section succession in the horizontal direction, and isolated blocks. Then, we used the AHP to classify basic weave patterns into three classes representing the fundamental weaves: plain, twill, and satin. Finally, the statistical approach used to evaluate the efficiency of the proposed method concerning classification showed high correlation values between the predicted results and the experimental values. This study has practical implications in the textile industry, especially in the clothing sector. The manufacturers can use the results to automatically identify the woven fabric patterns without using the manual examination method.
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Research context

OpenAlex topics: Industrial Vision Systems and Defect Detection · Image and Object Detection Techniques · Advanced Measurement and Detection Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Fashion and Textile Design, College of Arts and Design, Princess Nourah bint Abdulrahman University , P.O. Box 84428 , Riyadh , 11671 , Saudi Arabia

Textile Engineering Laboratory, Monastir University , LR11ES42, 5070 , Ksar Hellal , Tunisia

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