TY - GEN
T1 - An Analysis of RGB, Hue and Grayscale under Various Illuminations
AU - Fitriyah, Hurriyatul
AU - Wihandika, Randy Cahya
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Hue is an appearance parameter model which theoretically shows only color information. In cases where illumination varies from locations and conditions, the hue in HSV/HSL/HSI color space is theoretically remains alike. This study gives an experimental analysis on whether hue value is similar in various illuminations. Analysis of RGB and grayscale under the same situation are also presented. The experiment used objects which have primary colors of red, green and blue in several variation such as dark vs. light color, indoor vs. outdoor location and dark vs. bright illumination. The result shows that hue has standard deviation of <16 (range 0°-360°) for all variations. It is very small compared to RGB which has standard deviation of > 52 (range 0-255) for all variations. Moreover, RGB values dropped drastically under a very low light condition. An analysis on grayscale was also performed. It results that objects' color cannot be differentiated in this color-space. Grayscale differentiates object well when based on brightness as its value on brighter objects or illuminations were larger than darker object or illumination.
AB - Hue is an appearance parameter model which theoretically shows only color information. In cases where illumination varies from locations and conditions, the hue in HSV/HSL/HSI color space is theoretically remains alike. This study gives an experimental analysis on whether hue value is similar in various illuminations. Analysis of RGB and grayscale under the same situation are also presented. The experiment used objects which have primary colors of red, green and blue in several variation such as dark vs. light color, indoor vs. outdoor location and dark vs. bright illumination. The result shows that hue has standard deviation of <16 (range 0°-360°) for all variations. It is very small compared to RGB which has standard deviation of > 52 (range 0-255) for all variations. Moreover, RGB values dropped drastically under a very low light condition. An analysis on grayscale was also performed. It results that objects' color cannot be differentiated in this color-space. Grayscale differentiates object well when based on brightness as its value on brighter objects or illuminations were larger than darker object or illumination.
KW - Grayscale
KW - Hue
KW - Illumination Variation
KW - RGB
UR - https://www.scopus.com/pages/publications/85065240496
U2 - 10.1109/SIET.2018.8693160
DO - 10.1109/SIET.2018.8693160
M3 - Conference contribution
AN - SCOPUS:85065240496
T3 - 3rd International Conference on Sustainable Information Engineering and Technology, SIET 2018 - Proceedings
SP - 38
EP - 41
BT - 3rd International Conference on Sustainable Information Engineering and Technology, SIET 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Sustainable Information Engineering and Technology, SIET 2018
Y2 - 10 November 2018 through 12 November 2018
ER -