Characterizing fabric crease recovery through sequential image analysis

Crease recovery is the ability of a fabric to revert to its original condition after deformation or folding. This recovery process is intricately linked to several fabric properties, including fiber content, yarn structure, weave, fabric finish, and mechanical treatments. Based on the dynamic nature of crease recovery, this paper employs sequential image analysis to track the velocity of fabric crease recovery at different positions and extract simple metrics for measuring fabric shape retention. In each image, the contour of the creased sample is detected, and the contour is modeled by a Gaussian function to calculate its barycenter. The barycenter of a crease is the point in space where the mass of the crease is concentrated, reflecting the shape and position of the crease. During the recovery process, the translation of the barycenter of the creased sample can be determined from the sequential images, leading to the calculation of crease’s recovery velocity. Experimental results demonstrate a linear relationship between the barycentric velocity and logarithmic time. The slope of the resulting fit line, designated as the crease coefficient k , serves as a singular metric for assessing the fabric’s shape retention following the release of the crease. This methodology is benchmarked against traditional fabric crease behavior tests, including the draping coefficient, bending length, and crease recovery angle. It demonstrates that the crease coefficient k offers greater reliability and accuracy across tests on 10 diverse fabric samples, which varied in terms of fiber content, weave, yarn size, and density.