journal article·1999-02

Automatic Recognition of Fabric Weave Patterns by Digital Image Analysis

Tae Jin Kang, Chang Hoon Kim, Kyung Wha Oh

Textile Research Journal· Volume 69· Issue 2
Publisher page

Abstract

By using computer image processing and analysis, a system to detect both weave patterns and yarn color designs is developed in this study. The image of a woven fabric is captured by a Hitachi color CCD camera and converted into digital data by a Targa+32 board. Two images—transmitted and reflected—are used to detect weave patterns. From the transmitted images, warp and weft cross points and the sizes of the yarns are determined by analyzing gray value changes in both horizontal and vertical directions. Then the warp and weft crossed states are determined by analyzing the normalized aspect ratio of an ellipse-shaped image at crossed points of the fabric. Furthermore, from reflected images, the total number of yarn colors and their arrangements in the fabric are determined. An HSV color model differentiates or groups similar yarn colors. Consequently, the system allows the weave pattern, either colored or solid, and the color design of a fabric to be correctly recognized.
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Research context

OpenAlex topics: Industrial Vision Systems and Defect Detection · Optical measurement and interference techniques · Surface Roughness and Optical Measurements

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

Affiliations

Department of Fiber and Polymer Science, Seoul National University, Seoul, Korea

Department of Home Economics Education, Chung-Ang University, Seoul, Korea

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