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Comparative Study of Skin Color based Segmentation Techniques

Noor A. Ibraheem, Rafiqul Z. Khan, Mokhtar M. Hasan Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication: 2013
© 2012 by IJAIS Journal
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  1. Noor A Ibraheem, Rafiqul Z Khan and Mokhtar M Hasan. Article: Comparative Study of Skin Color based Segmentation Techniques. International Journal of Applied Information Systems 5(10):24-34, August 2013. BibTeX

    	author = "Noor A. Ibraheem and Rafiqul Z. Khan and Mokhtar M. Hasan",
    	title = "Article: Comparative Study of Skin Color based Segmentation Techniques",
    	journal = "International Journal of Applied Information Systems",
    	year = 2013,
    	volume = 5,
    	number = 10,
    	pages = "24-34",
    	month = "August",
    	note = "Published by Foundation of Computer Science, New York, USA"


Segmentation is the classification of the input colored image into skin and non-skin pixels based on skin color information. A wide range of applications that require the segmentation process as a preprocessing operation such as computer vision, face/ hand detection and recognition, medical image analysis, and pattern recognition. Color information is one of the simple cues used for detecting skin color, and the use of proper color space to represent color information of an image is a crucial decision. In this literature different segmentation techniques are presented, examples and comparison between the main three based segmentation techniques are given as well. Skin color modeling based statistical model is explained in detail, with discussion the combination with different segmentation techniques. The selection of appropriate segmentation method depends on the application and system environments. The performance of any segmentation algorithm is quantified using some benchmarking such as recall and precision coefficients, or by calculating the percentage of correct and false detection rates according to the complexion of the technique used.


  1. Robert M. Haralick, Linda G. Shapiro "Computer and Robot Vision", Addison-Wesley, Co. , Vol. 2, 1993.
  2. P. Daniel Ratna Raju, G. Neelima, K. Prasada Rao, "Image segmentation-MR Images Segmentation with A Modified Gaussian Mixture Model", International Journal of Computer Science and Information Technologies (IJCSIT), Vol. 2 (6) , pp. 2573-2578, 2011.
  3. Mantas Paulinas, Andrius Ušinskas, "A Survey of Genetic Algorithms Applications for Image Enhancement And Segmentation", Information Technology And Control, Vol. 36(3), 2007. Available: http://itc. ktu. lt/itc363/paulinas363. pdf
  4. Siddhartha Bhattacharyya,"A Brief Survey of Color Image Preprocessing and Segmentation Techniques", Journal of Pattern Recognition Research,Vol. 6(1), pp. 120-129, 2011. Available: http://www. jprr. org/index. php/jprr/article/viewFile/191/96
  5. Qiang Wu, Fatima Merchant, Kenneth R. Castleman, "Microscope Image Processing", Academic Press, pages 9, April 2008
  6. Wikipedia website.
  7. Luigi Lamberti, Francesco Camastra, "Real-Time Hand Gesture Recognition Using a Color Glove", the 16th international conference on Image analysis and processing: Part I (ICIAP'11), Springer-Verlag Berlin Heidelberg, pp. 365–373, 2011.
  8. Francesca Gasparini, Raimondo Schettini, "Skin Segmentation Using Multiple Thresholding", In Internet imaging VII, IS and T/SPIE, pp. 60610F-1-60610F-8. SPIE 2006. Available: http://www. ivl. disco. unimib. it/papers2003/EI06-EI109%20Skin-paper. pdf
  9. Yu-Hsiang Wang, "Tutorial: Image Segmentation", Graduate Institute of Communication Engineering National Taiwan University, Taipei, Taiwan. Available: http://disp. ee. ntu. edu. tw/meeting/%E6%98%B1%E7%BF%94/Segmentation%20tutorial. pdf
  10. Shuying Zhao, Wenjun Tan, Shiguang Wen, and Yuanyuan Liu, "An Improved Algorithm of Hand Gesture Recognition under Intricate Background", the First International Conference on Intelligent Robotics and Applications (ICIRA 2008),: Part I. Springer-Verlag Berlin Heidelberg, pp. 786–794, 2008. Doi:10. 1007/978-3-540-88513-9_85
  11. Sudeep Sarkar, Barbara Loeding, Ruiduo Yang, Sunita Nayak, Ayush Parashar, "Segmentation-robust Representations, Matching, and Modeling for Sign Language", IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 13-19, June 2011. Doi: 10. 1109/CVPRW. 2011. 5981695
  12. Zhan Gao, "Appearance-based Hand Gesture Detection", available: http://www. cs. auckland. ac. nz/courses/compsci705s1c/exams/SeminarReports/HandGesture_zgao014. pdf
  13. Sergio ´Alvarez, David F. Llorca, Gerard Lacey, Stefan Ameling, "Spatial Hand Segmentation Using Skin Color And Background Subtraction", Trinity College Dublin's Computer Science Technical Report, Dublin, November 2010, Available: http://www. scss. tcd. ie/publications/tech-reports/reports. 10/TCD-CS-2010-35. pdf
  14. Cheng-Chin Chiang, Wen-Kai Tai, Mau-Tsuen Yang, Yi-Ting Huang, Chi-Jaung Huang, "A novel method for detecting lips, eyes and faces in real time", Elsevier Real-Time Imaging, Vol. 9, pp. 277–287, 2003. Doi: 10. 1016/j. rti. 2003. 08. 003.
  15. Mokhtar M. Hasan, and Pramod K. Mishra, "Hand Gesture Modeling and Recognition using Geometric Features: A Review", Canadian Journal on Image Processing and Computer Vision Vol. 3(1), March 2012. Available: http://www. ampublisher. com/Mar%202012/IPCV-1203-015-Hand-Gesture-Modeling-Recognition-Geometric-Features-Review. pdf
  16. Ruiduo Yang, Sudeep Sarkar, "Gesture Recognition using Hidden Markov Models from Fragmented Observations", IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06), Vol. 1, 2006. Doi: 10. 1109/CVPR. 2006. 126
  17. Michael J. Jones, James M. Rehg, "Statistical Color Models with Application to Skin Detection", IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, June 1999. Doi; 10. 1109/CVPR. 1999. 786951
  18. L. Lucchese , S. K. Mitra, "Color Image Segmentation: A State-of-the-Art Survey", Indian national science academy, Vol. 67(2), pp. 207-221, 2001. Doi: 10. 1. 1. 84. 4896
  19. K S Deshmukh, , "Color image segmentation: a review", SPIE Second International Conference on Digital Image Processing, Vol. 7546, pp. 754624-754624-6, 2010. Singapore . Doi: 10. 1117/12. 856011
  20. W?adys?aw Skarbek , Andreas Koschan, "Color Image Segmentation: A Survey", Berlin, Germany, October 1994. Available: http://imaging. utk. edu/~koschan/paper/coseg. pdf
  21. Son Lam Phung, Abdesselam Bouzerdoum, Douglas Chai, "Skin Segmentation Using Color Pixel Classification: Analysis And Comparison", IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 148-154, Vol. 27( 1), January 2005.
  22. Jean-Christophe Terrillon, Mahdad N. Shirazi, Hideo Fukamachi, Shigeru Akamatsu, "Comparative Performance of Different Skin Chrominance Models and Chrominance Spaces for the Automatic Detection of Human Faces in Color Images", IEEE the Fourth International Conference on Automatic Face and Gesture Recognition 2000 (FG '00), 2000.
  23. M. Van den Bergh, E. Koller-Meier, F. Bosch´, L. Van Gool, "Haarlet-based Hand Gesture Recognition for 3D Interaction", Workshop on Applications of Computer Vision (WACV), pp. 1-8, 2009, doi: 10. 1109/WACV. 2009. 5403103
  24. N. A. Ibraheem, M. M. Hasan, R. Z. Khan, P. K. Mishra, "Understanding Color Model: A Review", ARPN Journal of Science and Technology, vol. 2(4): 265-275, May 2012.
  25. E. Stergiopoulou, N. Papamarkos, "Hand Gesture Recognition Using A Neural Network Shape Fitting Technique", Elsevier, Engineering Applications of Artificial Intelligence, vol. 22 pp. 1141–1158, 2009 . doi:10. 1016/j. engappai. 2009. 03. 008
  26. Paola Campadelli, Francesco Cusmai, Raffaella Lanzarotti, "A Color-Based Method For Face Detection", available: http://homes. dsi. unimi. it/~lanzarot/Articoli/IST2003. pdf
  27. Yikai Fang, Kongqiao Wang, Jian Cheng, Hanqing Lu, "A Real-Time Hand Gesture Recognition Method", IEEE, ICME, pp. 995-998, 2007. Available: http://www. nlpr. labs. gov. cn/2007papers/gjhy/gh45. pdf
  28. Xiaojin Zhu Jie Yang Alex Waibel, "Segmenting Hands of Arbitrary Color", IEEE the Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG '000), pp. 446 – 453, 2000. Doi: 10. 1109/AFGR. 2000. 840673
  29. WÃlodzimierz Kasprzak, Artur Wilkowski, and Karol Czapnik, "Hand Gesture Recognition in Image Sequences Using Active Contours and HMMs", Image Processing & Communications Challenges, Academy Publishing House EXIT, Warszawa 2009, pp. 248-255.
  30. S. E. Ghobadi, O. E. Loepprich, K. Hartmann, and O. Loffeld, "Hand Segmentation Using 2D/3D Images", conference of Image and Vision Computing New Zealand 2007, pp. 64–69, New Zealand, December 2007.
  31. Vaishali S. Kulkarni, S. D. Lokhande, "Appearance Based Recognition of American Sign Language Using Gesture Segmentation", International Journal on Computer Science and Engineering (IJCSE), pp. 560-565, Vol. 2(3), 2010.
  32. Thiago R. Trigo and Sergio Roberto M. Pellegrino, "An Analysis of Features for Hand-Gesture Classification", 17th International Conference on Systems, Signals and Image Processing (IWSSIP 2010), pp. 412- 415, 2010
  33. Yepeng Guan, Mingen Zheng, "Real-time 3D pointing gesture recognition for natural HCI", IEEE the seventh World Congress on Intelligent Control and Automation, pp. 2433–2436, June 2008. Doi: 10. 1109/WCICA. 2008. 4593304
  34. G. Awad, T. Coogan, J. Hann, A. Sutherland, "Real-Time Hand Gesture Segmentation, Tracking and Recognition", School of Computing, Dublin City University, Dublin 9, Ireland.
  35. Gorodnichy, Dimitry; Yogeswaran, A. , "Detection and Tracking of Pianist Hands and Fingers", IEEE The 3rd Canadian Conference on Computer and Robot Vision, pp. 63-63, June 2006. doi; 10. 1109/CRV. 2006. 26
  36. M. K. Viblis, K. J. Kyriakopoulos, "Gesture Recognition: The Gesture Segmentation Problem", Journal of Intelligent and Robotic System, vol. 28, pp. 151–158, June 2000. Doi: 10. 1023/A:1008101200733
  37. Shinji Tsuruoka, Akio Kinoshita, Tetsushi Wakabayashi, Yasuji Miyake, Muneaki Ishida, "Extraction of Hand Region and Specification of Finger Tips from Color Image", IEEE International Conference on Virtual Systems and MultiMedia (VSMM '97), pp. 206 – 211, Augest 1997, doi: 10. 1109/VSMM. 1997. 622348
  38. R. G. O' Hagan, A. Zelinsky, S. Rougeaux, "Visual Gesture Interfaces For Virtual Environments", Elsevier, interacting with computers, Vol. 14, pp. 231-250, 2002, doi: 10. 1016/S0953-5438(01)00050-9
  39. Junwei Han, George M. Award, Alistair Sutherland, and Hai Wu, "Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning", IEEE 7th International Conference on Automatic Face and Gesture Recognition (FGR'06), pp. 237 – 242, April 2006. Doi: 10. 1109/FGR. 2006. 27
  40. Mahmoud Elmezain, Ayoub Al-Hamadi, J¨org Appenrodt, and Bernd Michaelis, "A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition", World Academy of Science, Engineering and Technology, Vol. 41, 2008.
  41. M. -H. Yang and N. Ahuja, "Gaussian Mixture Model for Human Skin Color and Its Applications in Image and Video Databases," SPIE Storage and Retrieval for Image and Video Databases, vol. 3656, pp. 458-466, Jan. 1998. Doi: 10. 1117/12. 333865
  42. Rahman Farnoosh, Behnam Zarpak, "Image Segmentation Using Gaussian Mixture Model", International Journal of Engineering Science (IUST), pp. 29-32, Vol. 19(1-2), 2008.
  43. Krishna Kant Singh ,Akansha Singh, "A Study Of Image Segmentation Algorithms For Different Types Of Images", International Journal of Computer Science Issues IJCSI, Vol. 7(5) ,September 2010.
  44. Chapter 4 Segmentation. Available: http://www. bioss. ac. uk/staff/chris/ch4. pdf
  45. Fritz Albregtsen, "Region and Edge Based Segmentation", 2010.
  46. Vladimir Vezhnevets, Vassili Sazonov, Alla Andreeva, "A Survey on Pixel-Based Skin Color Detection Techniques", IN PROC. GraphiCon-2003. Available: http://graphics. cs. msu. ru/en/publications/text/gc2003vsa. pdf
  47. Son Lam Phung, Chai, D. , Bouzerdoum, A. , "A universal and robust human skin color model using neural networks", International Joint Conference on Neural Networks, (IJCNN '01), Washington, DC, July 2001. Doi: 10. 1109/IJCNN. 2001. 938827
  48. Jander Moreira, Luciano Da Fontoura Costa, "Neural-based color image segmentation and classification using self-organizing maps", 1996. Available: http://sibgrapi. sid. inpe. br/col/dpi. inpe. br/ambro/1998/04. 17. 15. 45/doc/a19. pdf
  49. Constantino Carlos Reyes-Aldasoro, Anal Aura Aldeco, "Image Segmentation and Compression Using Neural Networks", available http://www. cisst. org/~cista/446_2004/papers/SegAndCompression. pdf
  50. Bir Bhanu, Sungkee Lee, John Ming, "Adaptive Image Segmentation Using a Genetic Algorithm", IEEE transaction on systems, man , and cybernetics, Vol. 25(12), pp. 1543- 1567. December 1995.
  51. Demir Gokalp, "Learning Skin Pixels in Color Images Using Gaussian Mixture", available http://www. cs. bilkent. edu. tr/~guvenir/courses/cs550/Workshop/Demir_Gokalp. pdf
  52. Bertrand Scherrer, "Gaussian Mixture Model Classifiers", 2007.
  53. Mohand Saïd Allili, "A short tutorial on Gaussian Mixture Models", CRV 2010. available http://www. computerrobotvision. org/2010/tutorial_day/GMM_said_crv10_tutorial. pdf
  54. Shanthi Devara, Ron Kneusel, "Expectation-Maximization", CSCI 5454 Lecture 19 April 11, 2011.
  55. Nikhil R. Pal, Sankar K. Pal, "A Review on Image Segmentation Techniques", Elsevier Pattern Recognition Vol. 26(9), pp. 1277–1294, may 1993. doi: 10. 1016/0031-3203(93)90135-J.
  56. Noor Adnan Ibraheem. , Rafiqul Zaman Khan, "Vision Based Gesture Recognition Using Neural Networks Approaches: A Review", International Journal of Human Computer Interaction (IJHCI) Malaysia, Vol. 3(1), 2012.
  57. Hassana Grema Kaganami, Zou Beiji, "Region-Based Segmentation versus Edge Detection", IEEE Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 1217-1221, 2009. DOI: 10. 1109/IIH-MSP. 2009. 13
  58. http://homepages. inf. ed. ac. uk/rbf/CVonline/LOCAL_COPIES/RAMANI1/node19. html
  59. Bryan S. Morse, "Lecture 18: Segmentation (Region Based)", 2002.
  60. Image Segmentation, Lecture 16.
  61. Hebert Luchetti Ribeiro, Adilson Gonzaga, "Hand Image Segmentation in Video Sequence by GMM: a comparative analysis" IEEE on Computer Graphics and Image Processing (SIBGRAPI'06), 2006
  62. Stephen J. Mckenna, Shaogang gong, Yogesh Raja, "Modeling Facial Color and Identity with Gaussian Mixtures", Elsevier, April 1998.
  63. M. Krishnaveni, V. Radha, "Topological Derivative Based Image Segmentation For Sign Language Recognition System Using Isotropic Filter", International Journal of Computer Science and Information Security(IJCSIS), Vol. 6( 3), 2009.
  64. Nguyen N. T. , Bui T. D. , "Automated Posture Segmentation In Continuous Finger Spelling Recognition", IEEE 3rd International Conference on Human-Centric Computing, HumanCom 2010, August 2010. Cebu. Doi: 10. 1109/HUMANCOM. 2010. 5563311
  65. Qiulei Dong, Yihong Wu and Zhanyi Hu, "Gesture Segmentation from a Video Sequence Using Greedy Similarity Measure", IEEE 18th International Conference on Pattern Recognition (ICPR 2006). pp. 331 – 334, September 2006. doi: 10. 1109/ICPR. 2006. 608
  66. Yining Deng and B. S. Manjunath, "Unsupervised Segmentation of Color-Texture Regions in Images and Video", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23(8), August 2001. Doi: 10. 1109/34. 946985
  67. http://homepages. inf. ed. ac. uk/rbf/HIPR2/log. htm
  68. Rafiqul Zaman khan, Noor Adnan Ibraheem, "Survey on Gesture Recognition for Hand Image Postures", Canadian Center of Computer and Information Science, Vol. 5(3), pp. 110-121, May 2012. doi:10. 5539/cis. v5n3p110


Color Image Segmentation, Color Space, Pixel Based Segmentation, Edge Based Segmentation, Region Based Segmentation, Gaussian Mixture Model