Automatic fabric dimensional distortion measurement and wrinkle evaluation

Date

2001-05

Journal Title

Journal ISSN

Volume Title

Publisher

Texas Tech University

Abstract

Dimensional change and wrinkling are two of the most significant fabric quality factors, and thus their measurement and evaluation are very crucial to the textile industry. Currently, industrial fabric dimensional change measurements are done manually by technicians with rulers, and fabric wrinkling evaluation is performed by technicians by visually comparing the perceived wrinkling to a set of visual standards. Both methods are highly subjective and. therefore, not very accurate. In recent years, there has been an increasing demand from industry for the development of objective and automatic approaches to replace these methods. The content of this thesis is dedicated to discussing a novel, computer-aided method that was developed to automatically predict fabric shrinkage and wrinkle with very high accuracy.

Fabric shrinkage is measured as the percentage between the initial and final dimensions of the fabric specimen. To measure shrinkage, a pattern of benchmarks is drawn on fabric samples before they are washed. These marks serve as registration points to facilitate comparison before and after washing. Digital images of the marked fabric samples are obtained by scanning the samples with a standard flatbed scanner. The problem is to develop a computer program that can accurately locate the marks in the digital images regardless of the color of both the marks (since the color of the marks is chosen at random) and the samples. The program must also be robust in the presence of noise in the fabric, such as lint and dirt spots. By obtaining position translation of the marks drawn on the fabric before and after it is washed, shrinkage can be calculated. A detailed description of the methods used to accomplish these tasks is given in the thesis.

Description

Keywords

Textile fabrics, Computer vision

Citation