Real-time Segmentation of Yarn Images Based on an FCM Algorithm and Intensity Gradient Analysis
Journal Title: Fibres and Textiles in Eastern Europe - Year 2016, Vol 24, Issue 4
Abstract
This paper presents a new method for real-time segmentation of yarn images which are captured by a real-time image acquisition device. The first frame of the images is clustered by the local average intensity and entropy of the image based on the FCM (Fuzzy C-means) algorithm to obtain a segmentation threshold value. The pixels with an intensity below the threshold value in each column of the image are convolved with a convolve template to construct an intensity gradient curve. The points of maximum value and minimum value in the curve are considered as the upper and lower edge points of yarn. A robust real-time segmentation algorithm of yarn images is obtained for evaluating yarn diameter more precisely. Finally two indices of SE (Segmentation Error) in % and ADE (Average Diameter Error) in % are proposed to evaluate the segmentation method, which is then compared with the manual method.
Authors and Affiliations
Zhongjian Li, Ruru Pan, Jing’an Wang, Ziyu Wang, Bianbian Li, Weidong Gao
Keywords
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- EP ID EP90624
- DOI 10.5604/12303666.1201130
- Views 121
- Downloads 0
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