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Face Recognition Using the Novel Fuzzy-GIST Mechanism

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Book cover Proceedings of International Conference on Cognition and Recognition

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 14))

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Abstract

Face Recognition (FR) is one of the most thriving fields of contemporary research, and despite its universal application in authentication and verification systems, ensuring its effectiveness in unconstrained scenarios has predominantly remained an on-going challenge in Computer Vision, because FR systems experience considerable loss in performance, when there exists significant variation between the test and database faces in terms of attributes such as Pose, Camera Angle, Illumination and so on. The potency of FR systems markedly declines in the presence of noise in a given face and furthermore, the performance is also determined to a large degree by the Feature Extraction technique that is employed. Hence in this paper, we propose a novel mechanism known as Fuzzy-GIST, that can proficiently perform FR by adeptly handling real-time images (which contain the aforementioned unconstrained attributes) in low-powered portable devices by employing Fuzzy Filters to eliminate extraneous noise in the facial image, prior to feature extraction using the computationally less demanding GIST descriptor. Backed by relevant mathematical defense, we will establish the efficacy of our proposed system by conducting detailed experimentations on the ORL and IIT-K databases.

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References

  1. Biometrics (2016) http://www.cse.iitk.ac.in/users/biometrics/pages/face.htm. Accessed 03 July 2016

  2. Samal A, Iyengar PA (1992) Automatic recognition and analysis of human faces and facial expressions: A survey. Pattern Recogn 25(1):65–77

    Article  Google Scholar 

  3. Mou W, Gunes H, Patras I (2016) Automatic recognition of emotions and membership in group videos. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 27–35

    Google Scholar 

  4. Zhao W, Chellappa R, Phillips PJ, Rosenfeld A (2003) Face recognition: a literature survey. ACM Comput Surv (CSUR) 35(4):399–458

    Google Scholar 

  5. Cao F, Hu H, Lu J, Zhao, Zhou Z, Wu J (2016) Pose and illumination variable face recognition via sparse representation and illumination dictionary. Knowl Based Syst

    Google Scholar 

  6. Kikkeri HN, Koenig MF, Cole J (2016) Face recognition using depth based tracking. U.S. Patent 9,317,762, issued 19 Apr 2016

    Google Scholar 

  7. IIT Kanpur Face database (2016) http://www.face-rec.org/databases/. Accessed 03 July 2016

  8. Hassner T, Masi I, Kim J Choi J, Harel S, Natarajan P, Medioni G (2016) Pooling faces: Template based face recognition with pooled face images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp 59–67

    Google Scholar 

  9. Heisele B, Ho P, Wu J, Poggio T (2003) Face recognition: component-based versus global approaches. Comput Vis Image Underst 91(1–2):6–21

    Article  Google Scholar 

  10. Bhatt BG, Shah ZH (2011) Face feature extraction techniques: a survey. In: National conference on recent trends in engineering & technology, 13–14 May 2011

    Google Scholar 

  11. Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110

    Article  Google Scholar 

  12. Lowe DG (1999) Object recognition from local scale-invariant features. In: The proceedings of the seventh IEEE international conference on computer vision, 1999, IEEE, vol 2, pp 1150–1157

    Google Scholar 

  13. Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Computer Vis Image Unders 110(3):346–359

    Google Scholar 

  14. Bay H, Tuytelaars T, Van Gool L (2006) Surf: speeded up robust features. In: Computer vision–ECCV 2006. Springer, Berlin, pp 404–417

    Google Scholar 

  15. Calonder M, Lepetit V, Strecha C, Fua P (2010) BRIEF: binary robust independent elementary features. In: Proceedings of the European conference on computer vision (ECCV), 2010

    Google Scholar 

  16. Rosten E, Drummond T (2006) Machine learning for high-speed corner detection. In: European conference on computer vision, vol 1

    Google Scholar 

  17. Rublee E, Rabaud V, Konolige K, Bradski G (2011) ORB: an efficient alternative to SIFT or SURF. In: 2011 International conference on computer vision, IEEE, pp 2564–2571

    Google Scholar 

  18. Douze M, Jégou H, Sandhawalia H, Amsaleg L, Schmid C (2009) Evaluation of gist descriptors for web-scale image search. In: Proceedings of the ACM international conference on image and video retrieval, ACM, p 19

    Google Scholar 

  19. Oliva A, Torralba A (2001) Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis 42(3):145–175

    Article  MATH  Google Scholar 

  20. Oujaoura M, Minaoui B, Fakir M (2013) Walsh, texture and GIST descriptors with bayesian networks for recognition of Tifinagh characters. Int J Comput Appl 81(12)

    Google Scholar 

  21. Sikirić I, Brkić K, Šegvić S (2013) Classifying traffic scenes using the GIST image descriptor. arXiv preprint arXiv:1310.0316

  22. Arunkumar S, Akula RT, Gupta R (2009) Fuzzy filters to the reduction of impulse and gaussian noise in gray and color images. Int J Recent Trends Eng Technol 1(1)

    Google Scholar 

  23. Kwan, Benjamin YM, and Hon Keung Kwan. “Impulse noise reduction in brain magnetic resonance imaging using fuzzy filters.” World Academy of Science, Engineering and Technology 60 (2011): 1344–1347

    Google Scholar 

  24. Ali EH, Ekhlas HK, Mohammed MS. Mixed-noise reduction by using hybrid (Fuzzy & Kalman) filters for gray and color images

    Google Scholar 

  25. Hanji G, Basaveshwari C, Latte MV (2015) Novel fuzzy filters for noise suppression from digital grey and color images. Int J Comput Appl 125(15)

    Google Scholar 

  26. Kwan HK (2003) Fuzzy filters for noisy image filtering. In: Proceedings of the 2003 international symposium on circuits and systems, ISCAS’03, IEEE, vol 4, pp IV-161

    Google Scholar 

  27. Kumar A, Joshi A, Anil Kumar A, Mittal A, Gangodkar DR (2014) Template matching application in geo-referencing of remote sensing temporal image. Int J Signal Process Image Process Pattern Recogn 7(2):201–210

    Google Scholar 

  28. Kilthau SL, Drew MS, Möller T (2002) Full search content independent block matching based on the fast fourier transform. In: 2002 International conference on image processing. Proceedings, IEEE, vol 1, pp I-669

    Google Scholar 

  29. Vinay A, Gagana B, Shekhar VS, Anil B, Murthy KNB, Natarajan S (2016) A double filtered GIST descriptor for face recognition. Procedia Comput Sci 79:533–542

    Google Scholar 

  30. AT&T Database of Faces (2016) ORL face database. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html. Accessed 02 July 2016

  31. IIT Kanpur Face database (2016) http://www.iitk.ac.in/infocell/iitk/newhtml/storyoftheweek24.htm. Accessed 03 July 2016

  32. Uiboupin T, Rasti P, Anbarjafari G, Demirel H (2016) Facial image super resolution using sparse representation for improving face recognition in surveillance monitoring. In: 2016 24th signal processing and communication application conference (SIU), IEEE, pp 437–440

    Google Scholar 

  33. Sill M et al (2011) Robust bi-clustering by sparse singular value decomposition incorporating stability selection. Bioinformatics 27(15):2089–2097

    Google Scholar 

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Author information

Authors and Affiliations

  1. PES University, 100 Feet Ring Road, BSK 3rd Stage, Bengaluru, 560085, India

    A. Vinay, B. Gagana, Vinay S. Shekhar, Vasudha S. Shekar, K. N. Balasubramanya Murthy & S. Natarajan

Authors
  1. A. Vinay
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  2. B. Gagana
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  3. Vinay S. Shekhar
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  4. Vasudha S. Shekar
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  5. K. N. Balasubramanya Murthy
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  6. S. Natarajan
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Corresponding author

Correspondence to A. Vinay .

Editor information

Editors and Affiliations

  1. Department of Studies in Computer Science, University of Mysore, Mysore, Karnataka, India

    D. S. Guru

  2. Department of Master of Computer Application, Maharaja Institute of Technology, Mysore, Karnataka, India

    T. Vasudev

  3. Department of Computer Science and Engineering, Maharaja Institute of Technology, Mysore, Karnataka, India

    H.K. Chethan

  4. Department of Information Science and Engineering, Maharaja Institute of Technology, Mysore, Karnataka, India

    Y.H. Sharath Kumar

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Vinay, A., Gagana, B., Shekhar, V.S., Shekar, V.S., Balasubramanya Murthy, K.N., Natarajan, S. (2018). Face Recognition Using the Novel Fuzzy-GIST Mechanism. In: Guru, D., Vasudev, T., Chethan, H., Kumar, Y. (eds) Proceedings of International Conference on Cognition and Recognition . Lecture Notes in Networks and Systems, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-10-5146-3_36

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  • DOI: https://doi.org/10.1007/978-981-10-5146-3_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5145-6

  • Online ISBN: 978-981-10-5146-3

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