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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/45583
Title: Comparison of Fabric Color Naming Using RGB and HSV Color Models
Authors: Piyapat Charoensawan
Sukanya Phongsuphap
Ikuko Shimizu
Mahidol University
Tokyo University of Agriculture and Technology
Keywords: Computer Science
Issue Date: 6-Sep-2018
Citation: Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018. (2018)
Abstract: © 2018 IEEE. This paper aims to find an effective method for identifying colors of fabrics. We consider the following color naming models: Basic Color terms, ISCC-NBS Color system, Frery's Color name, and Fractals Lab's Ultimate color vocabulary. The appropriate color name is assigned for a fabric image by using seven types of minimum distance in RGB and HSV color models. Experiments are performed on S3 plain color fabric images. Results show that in general, the method of identifying fabric color name by using Frery's color name model with the color similarity measure by Euclidean distance in RGB space gives the better result than the other methods. When we analyze in more details by classifying fabric images into three groups based on color saturation, we found that the effective methods for color naming are as follows: Frery's color name model with the quadratic distance in HSV space works well for the group of low color saturation (96.23% accuracy). Frery's color name model with Euclidean distance in RGB space works well for the group of medium color saturation (81.82% accuracy). And Fractals Lab's Ultimate color vocabulary model with the weighted Euclidean distance in HSV space work good for the group of high color saturation (76.09% accuracy).
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85057712175&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/45583
Appears in Collections:Scopus 2018

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