Abstract
Fabric pilling evaluation has been considered as an essential element for textile quality inspection. Traditional manual method is still based on human eyes and brain, which is subjective with low efficiency. This paper proposes an objective evaluation method based on semi-calibrated near-light Photometric Stereo (PS). Fabric images are digitalized by self-developed image acquisition system. The 3D depth information of each point could be obtained by PS algorithm and then mapped to 2D grayscale image. After that, the non-textured image could be filtered by using the Gaussian low-pass filter. The pilling segmentation is conducted by using global iterative threshold segmentation method, and then K-Nearest Neighbor (KNN) is finally selected as a tool for the grade classification of fabric pilling. Our experimental results show that the proposed evaluation system could achieve excellent judging performance for the objective pilling evaluation.
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