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Real-time Segmentation of Yarn Images Based on an FCM Algorithm and Intensity Gradient Analysis

Research and development

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Nr DOI: 10.5604/12303666.1201130

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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.

Tags:

real-time segmentation, image processing, yarn evenness, FCM algorithm, gradient analysis.

Citation:

Li Z, Pan R, Wang J, Wang Z, Li B, Gao W. Real-time Segmentation of Yarn Images Based on an FCM Algorithm and Intensity Gradient Analysis. FIBRES & TEXTILES in Eastern Europe 2016; 24, 4(118): 45-50. DOI: 10.5604/12303666.1201130

Published in issue no 4 (118) / 2016, pages 45–50.

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