Development of a Face Detection Algorithm Based on Skin Segmentation and Facial Feature Extraction

Öz

 This paper presents a face detection algorithm capable of detecting face(s) without prior training as a face classifier. The technique employed in developing the algorithm is based on skin segmentation and facial feature extraction of the two eyes and mouth. Skin segmentation was done in the red, green, blue color space. White balance correction was employed to correct the change in image temperature that occurs due to change in lighting conditions at the point of acquiring image. Morphological operations and bounding box were employed to search and extract face region from the segmented skin region. Facial feature, eyes and mouth, were extracted for final verification of the sensed face using the Laplacian of Gaussian filter and the isosceles triangle matching rules. The extracted features were used to develop the face detection algorithm. The developed algorithm was evaluated using random images taken under different lighting conditions. Furthermore, the efficiency of the developed face detection algorithm was evaluated using a standard face detection image database. The result obtained shows that the developed face detection algorithm performed satisfactorily well with 81.37% detection accuracy. Furthermore, the results obtained from the performance evaluation of the developed face detection for this study has shown it clearly that accuracy detection of dissimilar faces in images with complex background is possible and attainable

Anahtar Kelimeler

• Face detection; face detection methods; skin segmentation; morphological operations; isosceles triangle matching

Kaynakça

1. S. Zafeiriou, C. Zhang, and Z. Zhang, “A survey on face detection in the wild: past. present and future”, Computer Vision and Image Understanding, vol. 138, pp. 1-24, 2015.
2. J. Jin, B. Xu, X. Liu, Y. Wang, L. Cao, L. Han, B. Zhou, and M. Li, “A face detection and location method based on feature binding” Signal Processing: Image Communication, vol. 36, pp. 179-189, 2015.
3. H. Pan, Y. Zhu, and L. Xia, “Efficient and accurate face detection using heterogeneous feature descriptors and feature selection”, Computer Vision and Image Understanding, vol. 117, pp. 12-28, 2013.
4. G. Onder, and A. Kayacik, “Multiview face detection using Gabor filters and support vector machine”, Technical Report, IDE0852, Bachlor Thesis in Computer System Engineering, School of Science, Computer and Electrical Engineering, Halmsted University, Sweden, 2008. Online [Available]: https://www.diva-portal.org/smash/get/diva2:239370/FULLTEXT01.pdf. Accessed on October 17, 2016.
5. D. Ghimire, and J. Lee, “A robust face detection method based on skin color and edges”, Journal of Information Process System, vol. 9, no. 1, pp. 141-156, 2013.
6. C. Lin, and K-C. Fan, “Triangle-based approach to the detection of human face”, Journal of Pattern Recognition, vol. 34, no. 6, pp. 1271-1284, 2001.
7. M.R Mahmoodi,. and S.M. Sayedi, “A face detection based on kernel probability map”, Computers and Electrical Engineering, vol. 46, pp. 205-216, 2015.
8. Y. Ban, S-K. Kim, S. Kim, K-A. Toh, and S. Lee, “Face detection based on skin color likelihood”, Pattern Recognition, vol. 47, pp. 1573-1585, 2014.

9. C.E. Erdem, S. Ulukaya, A., Karaali, and A.T. Erdem, “Combining HAAR feature and skin colour based classifier for face detection”, In Proceedings of IEEE International Conference on Acoustic Speech and Signal, Prague Congress Centre, Prague, Czech Republic, pp. 1497-1500, 22-27 May 2011.
10. M-H. Yang, D.J. Kriegman, and N. Ahuja, “Detecting faces in lmages: A survey”. IEEE Transactions On Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 34-58, 2002.
11. S.K. Singh, D.S. Chauhan, M. Vasta, and R Singh., “A robust skin colour based face detection algorithm”, Tamkang Journal of Science and Engineering, vol. 6, no. 4, pp. 227-234, 2003.
12. H-J. Lin, S-Y. Wang, S-H. Yen, and Y-T. Kao, “Face detection based on skin color segmentation and neural network”, In proceedings of IEEE International Conference on Neural Networks and Brain, Beijing, China, pp. 1144-1149, 13-15 October 2005.
13. Y. Wang, and B. Yuan, “A novel approach for human face detection from colour ımages under complex background”, Pattern Recognition, vol. 34, no. 10, pp. 1983-1992, 2001.
14. M. Tayyab, and M.F. Zafar, “Face detection using 2D-discrete cosine transform and back propagation neural network”, in Proceedings of IEEE Conference on Emerging Technologies, Islamabad, Pakistan, pp. 35-39, 19-20 October 2009.
15. J. Ruan, and J. Yin, “Face detection based on facial features and linear support vector machines”, In Proceedings of the International Conference on Communication Software and Networks, Chengdu, Sichuan, China, pp. 371-375, 27-28 Febuary 2009.
16. X. Liu, G. Geng, and X. Wang, “Automatically face detection based on bp neural network and bayesian decision”, in Proceedings of 6th IEEE International Conference on Natural Computation, Yantai, China, pp. 1590-1594, 10-12 August 2010.
17. C. Aiping, P. Lian, T. Yaobin, and N. Ning, “Face detection technology based on skin color segmentation and template matching. IEEE 2nd International Workshop on Education Technology and Computer. Wuhan, China, pp. 708-711, 6-7 March 2010.
18. Z. Li, L.Xue, and F. Tan, (2010). “Face detection ın complex background based on skin color features and ımproved adaboost algorithms”, IEEE International Conference on Progress in Informatics and Computing, Shanghai, China, pp. 723-727, 10-12 December 2010.
19. E. Hjelmas, and B.K. Low, “Face detection: A survey”, Computer Vision and Image Understanding, vol. 83, pp. 236-274, 2001.
20. H. Zhu, S. Zhou, J. Wang, and Z. Yin, “An algorithm of pornographic ımage detection”, in Proceedings of the 4th IEEE International Conference on Image and Graphics. Chengdu, Sichuan, China, pp. 801-804. 22-24 August 2007.
21. M.J. Taylor, and T. Morris, “Adaptive skin segmentation via feature-based face detection”, in Proceedings of International Society for Optics and Photonics, (SPIE Photonics) Brussels, Belgium, 14-17 April 2014. Online [Available]: http://www.cs.man.ac.uk/~tmorris/pubs/AdaptSS_SPIE.pdf. Accessed on 17 October 2016.
22. R.C. Mat, S. Azmi, R. Daud, A.N. Zulkifli, and F.K. Ahmad, “Morpholocal operation on printed circuit board (PCB) reverse Engineering using MATLAB”, in Proceedings of Knowledge Management International Conference and Exhibition, Legend Hotel Kuala Lumpur, Malaysia, pp. 529-533, 6-8 June 2006.
23. D. Chudasama, T. Patel, and S. Joshi, “Image segmentation using morphological operations”, International Journal of Computer Applications, vol. 117. no. 18, pp. 16-19, 2015.
24. A. Khanparde, S. Reddy, and S. Ravipudi, “Face detection using color based segmentation and morphological processing – a case study”, in Proceedings of the International Symposium on Computer Engineering and Technology, Mandi Gobindgarh, Punjab, India, pp. 147-151, 19-20 March 2010.
25. C. Gürel, “Development of a face Recognition System”, A Master of Science Thesis at the Atilim University, Ankara, Turkey, p. 81, 2011. Online [Available]: http://docplayer.net/2761592-Development-of-a-face-recognition-system-a-thesis-submitted-to-the-graduate-school-of-natural-and-applied-sciences-atilim-university-cahit-gurel.html. Accessed on October 20, 2016.
26. H. Rahman, nd J. Afrin, “Human face detection in colour ımages with complex background using triangular approach”, Global Journal of Computer Science and Technology Graphics and Vision, vol. 13, no. 4, pp. 45-50, 2013.
27. Y.C. See, N.M. Noor, and A.C. Lai, “Hybrid face detection with skin segmentation and edge detection”, in Proceedings of 3rd IEEE International Conference on Signal and Image Processing Applications.Melaka, Malaysia, pp. 406-411, 8-10 October 2013.
28. M. Khammari, and B. Chemesse, “Face detection in complex background of colour ımages using mixture gaussian model and neural network”, International Conference on System and Processing Information., Guelma, Algeria, 12 – 14 May 2013. Online [Available]: https://www.researchgate.net/profile/Chemesse_ennehar_Bencheriet/publication/257945701_Face_Detection_in_Complex_Background_of_Color_Images_Using_Mixture_Gaussian_Model_and_Neural_Network/links/02e7e53314aca3ee57000000.pdf. Accessed on October 17, 2016.
29. H. Rowley, S. Baluja, and T. Kanade, “Neural network-based face detection”, IEEE Transactions on Pattern Analysis and Machine intelligence, vol. 20, no. 1, pp. 23–38, 1998.
30. C. Garcia, and M. Delakis, “A neural network architecture for fast and robust face detection”, IEEE 16th International Conference on Pattern Recognition, Quebec City, Canada, vol. 2, pp. 44-47, 11-15 August 2002.
31. A. Mohamed, Y.W. Weng, J. Jiang, and S. Ipson, (2008). Face Detection Based Neural Networks Using Robust Skin Segmentation. In Proceedings of the 5th IEEE International conference on Multi-Systems, Signals and Devices. Amman, Jordan, pp. 1-5, 20-22 July 2008.