TY - GEN
T1 - Comparison of Fabric Color Naming Using RGB and HSV Color Models
AU - Charoensawan, Piyapat
AU - Phongsuphap, Sukanya
AU - Shimizu, Ikuko
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/6
Y1 - 2018/9/6
N2 - 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).
AB - 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).
KW - Color image analysis
KW - Color naming
KW - Color similarity
KW - Fabric images
UR - https://www.scopus.com/pages/publications/85057712175
U2 - 10.1109/JCSSE.2018.8457329
DO - 10.1109/JCSSE.2018.8457329
M3 - Conference contribution
AN - SCOPUS:85057712175
T3 - Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018
BT - Proceeding of 2018 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018
A2 - Sawangphol, Wudhichart
A2 - Mitrpanont, Jarernsri
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Joint Conference on Computer Science and Software Engineering, JCSSE 2018
Y2 - 11 July 2018 through 13 July 2018
ER -