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Real-time iris detection

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Abstract

A real-time algorithm to automatically detect human faces and irises from color images has been developed. A Haar cascade-based algorithm has been applied for simple and fast face detection. The face image is then converted into a gray-scale image. Three types of image processing techniques have been tested to study their effect on the performance of the iris detection algorithm. Then iris candidates are extracted from the valley of the face region. The iris candidates are paired up and the cost of each possible pairing is computed by a combination of mathematical models. The pairing with the lowest cost is considered to be a pair of irises. The algorithm has been tested by quality images from a Logitech camera and noisy images from a Voxx CCD camera. The proposed algorithm has achieved a success rate of 83.60% for iris detection in an open office environment.

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References

  1. Tsuyoshi K, Mohamed R (2003) Iris detection using intensity and edge information. Pattern Recognition 36:549–562

    Article  Google Scholar 

  2. Chew WJ, Ang LM, Seng KP (2008) Automatic model-based face feature detection system. Proceedings of the International Symposium on Information Technology, pp 1–6

  3. Chai TY, Mohamed R, Woo SS, et al (2008) Automated detection of face and facial features. The 7th WSEAS International Conference on Signal Processing, Robotics and Automation, University of Cambridge, pp 230–234

  4. Balasubramaniam M, Palanivel S, Ramalingam V (2008) Real time face and mouth recognition using radial basis function neural networks. Expert Syst Appl pp 1–8

  5. Beymer DJ (1994) Face recognition under varying poses. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Seattle, WA, pp 756–761

  6. Li CM, Li YS, Zhuang QD, et al (2004) The face localization and regional features extraction. Proceedings of the 3rd International Conference on Machine Learning and Cybernetics, Shanghai, pp 26–29

  7. Brunelli R, Poggio T (1993) Face recognition: features versus templates. IEEE Trans Pattern Anal Mach Intell 15(10):1042–1052

    Article  Google Scholar 

  8. Hua G, Guangda S, Cheng D (2003) Feature points extraction from faces. Image and vision computing. Palmerston North, NZ

  9. Yu S, Kun H, Zhou J, et al (2004) Multi-resolution feature extraction in the human face. Proceedings of the International Conference on Information Acquisition

  10. Selin B, Bulut MM, Volkan A (2002) Projection-based method for segmentation of the human face and its evaluation. Pattern Recognition Lett 23:1623–1629

    Article  MATH  Google Scholar 

  11. Ryu YS, Oh SY (2001) Automatic extraction of eye and mouth fields from a face image using eigenfeatures and multilayer perceptrons. Pattern Recognition 34:2459–2466

    Article  MATH  Google Scholar 

  12. Karin S, Ioannis P (1998) A novel method for automatic face segmentation, facial feature extraction and tracking. Signal Process: Image Commun 12:263–281

    Article  Google Scholar 

  13. Wong KW, Lam KM, Siu WC (2001) An efficient algorithm for human face detection and facial feature extraction under different conditions. Pattern Recognition 34

  14. Zhao Y, Shen X, Georganas ND (2008) Combining integral projection and gabor transformation for automatic facial feature detection and extraction. Proceedings of the IEEE International Workshop on the Haptic Audio-visual Environment and its Applications, pp 103–107

  15. Stephen MS, Michael BJ (1997) SUSAN: a new approach to low level image processing. Int J Comput Vision 23(1):45–78

    Article  Google Scholar 

  16. Mauricio H, Geovanni M (2004) Facial feature extraction based on the smallest univalue segment assimilating nucleus (SUSAN) algorithm. Image Processing and Computer Vision Research Laboratory (IPCV-LAB), Escuela de Ingenieria Electrica, Universidad de Costa Rica

  17. Yulu Q, Goenawan B, Nuanwan S (1998) Finding the estimated position of facial features on the human face using intensity computation. IEEE Asia-Pacific Conference (APCCAS), pp 579–582

  18. Vladimir V (2002) Face and facial feature tracking for natural human-computer interface. International Conference Graphicon, Nizhny Novgorod, Russia

  19. Jie Y, Alex W (1996) A real-time face tracker. Application of Computer Vision, WACV’96, pp 142–147

  20. Erukhimov V, Lee KC (2008) A bottom-up framework for robust facial feature detection. Proceedings of the 8th International Conference on Automatic Face and Gesture Recognition, pp 1–5

  21. Kumatani K, Ekenel HK, Gao H, et al (2008) Multi-stream Gaussian mixture model based facial feature localization. Proceedings of the Signal Processing, Communications and Applications Conference, pp 1–4

  22. Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vision 57(2):137–154

    Article  Google Scholar 

  23. Tan X, Triggs B (2007) Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE International Workshop on Analysis and Modelling of Faces and Gestures, pp 235-249

  24. Liu H, Gao W, Miao J, et al (2002) A novel method to compensate variety of illumination in face detection. Joint Conference on Information Sciences, pp 692–695

  25. Sternberg SR (1986) Grayscale morphology. Comput Vision Graphics Image Process 35:333–355

    Article  Google Scholar 

  26. Fukui K, Yamaguchi O (1997) Facial feature point extraction method based on a combination of shape extraction and pattern matching. Trans IEICE Jpn J80-D-II(8):2170–2177

    Google Scholar 

  27. Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8(6):679–698

    Article  Google Scholar 

  28. Kawaguchi T, Hidaka D, Rizon M (2005) Detection of eyes from human faces by Hough transform and separability filter. Proceedings of IEEE International Conference on Image Processing, pp 49–52

  29. Lin CH, Wu JL (1999) Automatic facial feature extraction by genetic algorithms. IEEE Trans Image Process 8(6):834–845

    Article  Google Scholar 

  30. Martinez AM, Benaventa R (1998) The AR face database. CVC Technical Report No. 24

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Author information

Authors and Affiliations

  1. Department of Biomedical Technology, King Saud University, PO Box 10219, Riyadh, 11433, Kingdom of Saudi Arabia

    Mohamed Rizon & Ali AlMejrad

  2. Department of Mechatronic and Biomedical Engineering, Universiti Tunku Abdul Rahman (UTAR), Kuala Lumpur, Malaysia

    Chai Tong Yuen

  3. Advanced Laboratory for Intelligent Systems Research, Department of Computer Engineering, King Saud University, Riyadh, Kingdom of Saudi Arabia

    Naif Alajlan

Authors
  1. Mohamed Rizon
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  2. Chai Tong Yuen
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  3. Ali AlMejrad
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  4. Naif Alajlan
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Corresponding author

Correspondence to Mohamed Rizon.

Additional information

This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

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Rizon, M., Yuen, C.T., AlMejrad, A. et al. Real-time iris detection. Artif Life Robotics 15, 296–301 (2010). https://doi.org/10.1007/s10015-010-0811-x

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  • DOI: https://doi.org/10.1007/s10015-010-0811-x

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