Automatic Recognition of Fabric Weave Patterns by Digital Image Analysis

TLDR

The study develops a computer vision system to detect woven fabric patterns and yarn color designs. The system captures transmitted and reflected images of a fabric with a CCD camera, analyzes gray‑value changes and ellipse aspect ratios at warp‑weft cross points to identify weave patterns, and uses an HSV color model on reflected images to determine yarn colors. The system correctly recognizes both the weave pattern (colored or solid) and the color design of a fabric.

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.