Color Space to Detect Skin Image: The Procedure and Implication
(1) Universitas Diponegoro
(2) Universitas Diponegoro
(3) Universitas Diponegoro
Abstract
Skin detection is one of the processes to detect the presence of pornographic elements in an image. The most suitable feature for skin detection is the color feature. To be able to represent the skin color properly, it is needed to be processed in the appropriate color space. This study examines some color spaces to determine the most appropriate color space in detecting skin color. The color spaces in this case are RGB, HSV, HSL, YIQ, YUV, YCbCr, YPbPr, YDbDr, CIE XYZ, CIE L*a*b*, CIE L*u* v*, and CIE L*ch. Based on the test results using 400 image data consisting of 200 skin images and 200 non-skin images, it is obtained that the most appropriate color space to detect the color is CIE L*u*v*.
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Asmare, M.H., Asirvadam, W.S, Iznito, L. 2009. Color Space Selection for
Color Image Enhancement Applications. Proceeding of International
Conference on Signal Acquisition and Processing (ICSAP) 2009.
KualaLumpur, Malaysia, 3-5 April 2009
Vasthi, P. I., & Kusumaningrum, R. 2015. Object segmentation for fruit
images using OHTA colour space and cascade threshold. In Science in
Information Technology (ICSITech), 2015 International Conference on (pp.
-325). IEEE.
Isa, S.M., Mariana, F. 2009.Deteksi Citra Pornografi Menggunakan TSL Color
Space dan Nudity Detection Algorithm. Prosiding. Seminar Nasional
Informatika 2009 UPN Veteran Yogyakarta. Yogyakarta, Indonesia, 23 Mei
Zhuo, L., Geng, Z., Zhang, J., & guang Li, X. 2016. ORB feature based web
pornographic image recognition. Neurocomputing, 173(3), 511-517.
Stricker, M., Orengo, M. 1995. Similarityof Color Images. Proceedings SPIE
SPIE's Symposium on Electronic Imaging: Science and Technology. San
Jose, CA, United, March 23.
Rapid Tables.2017. RGB to HSV Color Conversion. (Online) (http://www.
rapidtables.com/convert/color/rgb-to-hsv.htm, diakses 19 Agustus 2017)
EEMBC. 2006. RGB to YIQ Conversion. (Online) (https://www.eembc.org/
techlit/datasheets/yiq_consumer.pdf, diakses 19 Agustus 2017)
Schweyer, M. 2015. Color Corversion. (Online) (http://www.equasys.
decolorcon version.html, diakses 19 Agustus 2017)
Shi, Y. Q., Sun, H. 2000. Image and Video Compression for Multimedia
Engineering. CRC Press, United States of America
Ford, A., Roberts, A. 1998.Colour Space Conversions. (Online) (http://www.
poynton.com/PDFs/coloureq.pdf, di akses 8 September 2017)
Endah, S. N., & KN, D. M. 2012. Klasifikasi Ucapan Kata dengan Support
Vector Machine. Jurnal Masyarakat Informatika, 3(6), 7-14.
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Scientific Journal of Informatics (SJI)
p-ISSN 2407-7658 | e-ISSN 2460-0040
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