Digital Image Analysis for Fabric Assessment
Source abstract
Abstract
Conventional methods of fabric inspection are tedious and require close association. In this work, digital image analysis for fabric assessment (DIAFA) is applied to modem and historic fabrics. Fabric images are divided into arrays of pixels with peak intensities distributed over gray scale ranges (histograms) and along constructed lines (line profiles). Fabric cover is measured by segmenting a histogram's B/w pixels, yarn spacing, and yarn thickness from moving point averages by calculating the breadth of a peak corresponding to an individual yarn at half the maximum peak height for a given line profile. The results show very good agreement with known values ( r = 0.919, n = 30, p < 0.01). Fourier power spectra provide facile measurements of yarn parameters in close agreement with the results from line profiling. With DIAFA, a small tool kit is developed to assist in the objective analysis of the structural integrity of fabrics in the museum environment, and it could be very useful in advancing automated fabric inspection.
Source: crossref · Quality: baseline
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
USDA, ARS, Eastern Regional Research Center, Wyndmoor, Pennsylvania 19038, U.S.A.
References (17)
Show source-provided references
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