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Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China
Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China
Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China
Intelligence Control and Simulation Laboratory, Department of Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Republic of China
In this paper, a novel approach to color and pattern analysis is proposed for printed fabric. An unsupervised analysis method is developed using a fuzzy C-means (FCM) clustering algorithm and a specific cluster-validity criterion (SC criterion). First, the printed fabric is captured by a color scanner and converted into full color digital files, then the mean filter is used to smooth the color of the image. The search for good cluster numbers is made by the SC criterion, and the corresponding color clusters are obtained based on the FCM clustering algorithm. Finally, the color and pattern features of the printed fabric are calculated. The experimental results show that this approach is very suitable for analyzing the colors and patterns of printed fabrics.
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