Published July 10, 2017
| Version v1
Journal article
Open
AUTOMATIC FACE DETECTION USING GENETIC ALGORITHM FOR VARIOUS CHALLENGES
Authors/Creators
- 1. Department of ECE, PEC University of Technology, Chandigarh
Description
Face detection in various conditions such as illumination, occlusion, complex background and different pose angles plays the most important role in face recognition. In this research, we proposed an improved algorithm for automatic live facial expression detection (FED) using radial basis function. Detect edges of the facial image by Genetic Algorithm and Fuzzy-C-means (GAFCM). The experimental results used various types of databases i.e. JAFFE, FEI, LFW-a, BioID, CMU and Own database. In this algorithm, detect a face using the fdlibmex algorithm. But we improved limitations of this algorithm using contrast enhancement. We solved the problem of low contrast images. In the preprocessing stage, apply median filtering for removing noise from an image. The detection rate has reached up to100% for expression recognition.
Files
171.pdf
Additional details
References
- 1. Sandeep Kumar, Sukhwinder Singh, and Jagdish Kumar, "A Study on Face Recognition Techniques with Age and Gender Classification", In IEEE International Conference on Computing, Communication and Automation (ICCCA), 5th-6th May 2017. 2. Sandeep Kumar, Sukhwinder Singh, and Jagdish Kumar, "A Comparative Study on Face Spoofing Attacks", In IEEE International Conference on Computing, Communication and Automation (ICCCA), 5th-6th May 2017. 3. Sandeep Kumar, Deepika, and Munish Kumar, "An Improved Face Detection Technique for a Long Distance and Near-Infrared Images", The Advances in Computational Sciences and Technology, vol, no. , pp, 2017. 4. Hatem, Hiyam, Zou Beiji, and Raed Majeed. "A Survey of Feature Base Methods for Human Face Detection." International Journal of Control and Automation 8, no. 5 (2015): 61-78. 5. Ghimire, Deepak, and Joonwhoan Lee. "A robust face detection method based on skin color and edges." Journal of Information Processing Systems 9, no. 1 (2013): 141-156. 6. PENG Lei (ID: 03090345)," Adaptive Median Filtering", 140.429 Digital Image Processing. 7. M. Srinivas, Lalit M. Patnaik, "Genetic Algorithms: A Survey". 8. D. E. Goldberg, Genetic Algorithms in Search, Optimization an Machine Learning, Addison-Wesley, 1989. 9. Amiya Halder, Arindam Kar, and Soumajit Pramanik," Histogram-based Evolutionary Dynamic Image Segmentation", 4th (ICECT 2012),pp-585-589. 10. Yap, Moi Hoon, Hassan Ugail, Reyer Zwiggelaar, Bashar Rajoub, Victoria Doherty, Stephanie Appleyard, and Gemma Hurdy. "A short review of methods for face detection and multifractal analysis." The IEEE International Conference on Cyber Worlds, pp. 231-236, 2009. 11. Michael J. Lyons, Shigeru Akemastu, Miyuki Kamachi, Jiro Gyoba "Coding Facial Expressions with Gabor Wavelets" 3rd IEEE International Conference on Automatic Face and Gesture Recognition, pp. 200-205 (1998). 12. E. Z. Tenorio and C. E. Thomaz. Analise multilinear discriminate de format frontais de Imagens 2D face. In Proceedings of the X Simposio Brasileiro de Automacao Intelligence SBAI 2011, pp. 266-271, Universidade Federal de Sao Joao del Rei, Sao Joao del Rei, Minas Gerais, Brazil, 18th - 21st September 2011. 13. C. E. Thomaz and G. A. Giraldi. A new ranking method for Principal Components Analysis and its application to face image analysis, Image and Vision Computing, vol. 28, no. 6, pp. 902-913, June 2010. 14. V. Amaral, C. Figaro-Garcia, G. J. F. Gattas, C. E. Thomaz. "Normalization especial de Imagens frontais deface em ambient control does e nao-control adds" (in Portuguese), Periodico Cientifico Electronic da FATEC Sao Caetano do Sul (FaSCi-Tech), vol. 1, no. 1, October 2009. 15. V. Amaral and C. E. Thomaz. "Normalization Espacial de Imagens Frontis de Face". Technical Report 01/2008 (in Portuguese), Department of Electrical Engineering, FEI, São Bernardo do Campo, São Paulo, Brazil, October 2008. 16. L. L. de Oliveira Junior and C. E. Thomaz. "Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro". Undergraduate Technical Report (in Portuguese), Department of Electrical Engineering, FEI, São Bernardo do Campo, São Paulo, Brazil, June 2006. 17. Lior Wolf, Tal Hassner, and Yaniv Taigman, Effective Face Recognition by Combining Multiple Descriptors and Learned Background Statistics, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(10), Oct. 2011. 18. Lior Wolf, Tal Hassner, and Yaniv Taigman, Similarity Scores based on Background Samples, Asian Conference on Computer Vision (ACCV), Xi' a Sept 2009. 19. Yaniv Taigman, Lior Wolf, and Tal Hassner, Multiple One-Shots for Utilizing Class Label Information, The British Machine Vision Conference (BMVC), London, Sept 2009. 20. Schneiderman, Henry, and Takeo Kanade. "A statistical method for 3D object detection applied to faces and cars." In Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, vol. 1, pp. 746-751. IEEE, 2000. 21. Schneiderman, Henry, and Takeo Kanade. "A histogram-based method for detection of faces and cars." In Image Processing, 2000. Proceedings. 2000 International Conference on, vol. 3, pp. 504-507. IEEE, 2000. 22. Schneiderman, Henry, and Takeo Kanade. "Probabilistic modeling of local appearance and spatial relationships for object recognition." In Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on, pp. 45-51. IEEE, 1998. 23. Rowley, Henry A., Shumeet Baluja, and Takeo Kanade. "Neural network-based face detection." IEEE Transactions on pattern analysis and machine intelligence 20, no. 1 (1998): 23-38. 24. Rowley, Henry A., Shumeet Baluja, and Takeo Kanade. "Rotation invariant neural network-based face detection." In Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on, pp. 38-44. IEEE, 1998.