Abstract
Security methods based on biometrics have been gaining importance increasingly in the last few years due to recent advances in biometrics technology and its reliability and efficiency in real world applications. Also, several major security disasters that occurred in the last decade have given a new momentum to this research area. The successful development of biometric security applications cannot only minimise such threats but may also help in preventing them from happening on a global scale. Biometric security methods take into account humans’ unique physical or behavioural traits that help to identify them based on their intrinsic characteristics. However, there are a number of issues related to biometric security, in particular with regard to the poor visibility of the images produced by surveillance cameras that need to be addressed. In this paper, we address this issue by proposing an integrated image enhancement approach for face detection. The proposed approach is based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It can adjust the colour cast and maintain the luminance of the whole image at the same level. We evaluate the performance of the proposed approach by applying three face detection methods (skin colour based face detection, feature based face detection and image based face detection) to surveillance images before and after enhancement using the proposed approach. The results show a significant improvement in face detection when the proposed approach was applied.
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References
Ahrens B (2005) Genetic algorithm optimization of superresolution parameters. In: GECCO ’05 genetic and evolutionary computation conference, 25–29 June 2005, Washington, DC, USA
Al-Manea A, El-Zaart A (2007) Contrast enhancement of MRI images. In: Lecture notes in computer science (LNCS). Springer, Berlin, pp 255–258
An G, Wu J, Ruan Q (2010) An illumination normalization model for face recognition under varied lighting conditions. Pattern Recognit Lett 31:1056–1067
Becsi T, Peter T (2006) A mixture of distributions background model for traffic video surveillance. Period Polytech Ser Transp Eng 34(1–2):109–117
Bianco S, Ciocca G, Cusano C, Schettini R (2010) Automatic color constancy algorithm selection and combination. Pattern Recognit 43:695–705
Burger W, Burge MJ (2008) Digital image processing, an algorithmic introduction using JAVA. Springer, Berlin. ISBN: 978-1-84628-379-6
Çavuşoğlu A, Görgünoğlu S (2008) A fast fingerprint image enhancement algorithm using a parabolic mask. Comput Electr Eng 34(3):250–256
Chauhan BS, David E, Datta PK (2005) Sensors for desert surveillance. Def Sci J 55(4):493–503
Chen S, Berglund E, Bigdeli A, Sanderson C, Lovell B C (2008) Experimental analysis of face recognition on still and cctv images. In: Proceedings of IEEE international conference on advanced video and signal based surveillance, pp 317–324
Chikane V, Fuh CS (2006a) Automatic white balance for digital still cameras. J Inf Sci Eng 22:497–509
Chikane V, Fuh CS (2006b) White balance method. United States Patent 20060164521, 27
Fisher R, Perkins S, Walker A, Wolfart E (2003) Contrast stretching. http://homepages.inf.ed.ac.uk/rbf/HIPR2/stretch.htm. Accessed 25 Sept 2010
Hasan SF, Stauder J, Trémeau A (2011) Robust color correction for stereo. In: The 8th European conference on visual media production, 16–17 November 2011, London, UK
Hatakeyama Y, Kawamoto K, Nobuhara H, Yoshida SI, Hirota K (2005) Color restoration algorithm for dynamic images under multiple luminance conditions using correction vectors. Pattern Recognit Lett 26(9):1304–1315
Jain AK, Ross A, Prabhakar S (2004) An introduction to biometric recognition. IEEE Trans Circuits Syst Video Technol 14(1):4–20
Kao WC, Hsu MC, Yang YY (2010) Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition. Pattern Recognit Lett 43(5):1736–1747
Kim C, O’Connor NE (2009) Using the discrete hadamard transform to detect moving objects in surveillance video. In: International conference on computer vision theory and applications, 5–8 February 2009, Porto, Portugal
Kim Y, Teoh ABJ, Toh KA (2010) A performance driven methodology for cancelable face templates generation. Pattern Recognit 43:2544–2559
Montabone S (2010) Beginning digital image processing: using free tools for photographers. Apress, Berkely. ISBN: 9781430228417
Moreno AB, Sánchez A, Frías-Martínez E, Vélez JF (2010) Three-dimensional facial surface modeling applied to recognition. Eng Appl Artif Intell 22(8):1233–1244
Mudigoudar R, Bagal S, Yue Z, Lakshmi P, Topiwala P (2009) Video super-resolution: from QVGA to HD in real-time. In: Applications of digital image processing XXXII. Proceedings of the SPIE, vol 7443, pp 74430W–74430W12
Sahoolizadeh H, Sarikhanimoghadam D, Dehghani H (2008) Face detection using Gabor wavelets and neural networks. World Academy of Science, Engineering and Technology
Santhaseelan V, Asari VK (2011) Phase congruency based technique for the removal of rain from video. Image analysis and recognition. Lect Notes Comput Sci 6753:30–39
Schweng and Detlef (2006) Hexagonal color pixel structure with white pixels. United States Patent 20060146064
Smids M (2006) Background subtraction for urban traffic monitoring using webcams. Master Thesis, Universiteit van Amsterdam, FNWI
Tehrani MP, Ishikawa A, Sakazawa S, Koikea A (2010) Iterative colour correction of multicamera system using corresponding feature points. J Vis Commun Image Represent 21(5–6):377–391
Von Kries J (1902) ‘Chromatic adaptation’, Festschrift der Albrecht-Ludwig-Universität, Fribourg [Translation: MacAdam DL (1970) Sources of color science. MIT Press, Cambridge]
Wang J, Zhang C, Shum HY (2004) Face image resolution versus face recognition performance based on two global methods. In: Proceeding of Asian conference on computer vision. Jeju Island, Korea
Wang ZG, Liang ZH, Liu CL (2009) A real-time image processor with combining dynamic contrast ratio enhancement and inverse gamma correction for PDP. Displays 30(3):133–139
Weijer JVD, Gevers T, Gijsenij A (2007) Edge-based color constancy. IEEE Trans Image Process 16(9):2207–2214
Weng CC, Chen H, Fuh CH (2005) A novel automatic white balance method for digital still cameras. In: IEEE international symposium on circuits and systems, international conference Center Kobe in Japan, vol 4, pp 3801–3804
Wong A, Bishop W (2007) Simultaneous gamma correction and registration in the frequency domain. In: Proceedings of the 2007 international conference on image processing, computer vision & pattern recognition, IPCV 2007, 25–28 June 2007, Las Vegas, NV, USA, pp 145–151
Wu J, Wei Z, Chang Y (2010) Color and texture feature for content based image retrieval. Int J Digit Content Technol Appl 4(3)
Yap MH, Ugail H, Zwiggelaar R, Rajoub B, Doherty V, Appleyard S, Hurdy G (2009) A short review of methods for face detection and multifractal analysis. In: International conference on cyberworlds, 07–11 Sept 2009, Bradford, West Yorkshire, UK
Zhang L, Zhang L, Shen H, Li P (2010) A super-resolution reconstruction algorithm for surveillance images. Signal Process 90(3):848–859
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Iqbal, K., Odetayo, M.O. & James, A. Face detection of ubiquitous surveillance images for biometric security from an image enhancement perspective. J Ambient Intell Human Comput 5, 133–146 (2014). https://doi.org/10.1007/s12652-012-0134-y
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DOI: https://doi.org/10.1007/s12652-012-0134-y