Evaluating Fabric Pilling with Light-Projected Image Analysis

Abstract

An innovative method and a device for objectively evaluating fabric pilling grade based on light projection using image analysis is presented in this paper. The method can eliminate interference with pilling information from fabric color and pattern. The device for acquiring light-projected images, detecting the profile of projected images, segmenting pills appearing on converted gray images, extracting of a pill's feature index, and so on are discussed in detail. Pilling grade is assessed by a Kohonen self-organizing feature map neural network. Thirty different kind of pilled fabric samples are trained and tested, and the correlation coefficient between the objective grade and subjective grade is 0.94 for the training samples and 1 for the testing samples. The sample number with ± I grade deviation is 5, so the objective inspection accuracy is 83%.

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