Open Access
Issue
E3S Web Conf.
Volume 351, 2022
10th International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES’2022)
Article Number 01033
Number of page(s) 5
DOI https://doi.org/10.1051/e3sconf/202235101033
Published online 24 May 2022
  1. A. Hassouneh, A. M. Mutawa, and M. Murugappan, “Development of a Real-Time Emotion Recognition System Using Facial Expressions and EEG based on machine learning and deep neural network methods,” Inform. Med. Unlocked, vol. 20, pp. 100372, 2020. [CrossRef] [Google Scholar]
  2. A. Chaudhary and S. S. Singh, “Lung Cancer Detection on CT Images by Using Image Processing,” in 2012 International Conference on Computing Sciences, Phagwara, India, Sep 2012, pp. 142–146. [CrossRef] [Google Scholar]
  3. M. S. Al-Tarawneh, “Lung Cancer Detection Using Image Processing Techniques”, no. 20, p. 13, 2012. [Google Scholar]
  4. U. B. Ansari and T. Sarode, “Skin Cancer Detection Using Image Processing”, vol. 04, no [Google Scholar]
  5. 04, p. 7. [Google Scholar]
  6. C. L. Deepika, M. Alagappan, A. Kandaswamy, H. Wassim Ferose, and R. Arun, “Automatic, Robust Face Detection and Recognition System for Surveillance and Security Using LabVIEW (sCUBE),” in Advances in Digital Image Processing and Information Technology, vol. 205, D. Nagamalai, E. Renault, and M. Dhanuskodi, eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 146–155. DOI: 10.1007/978-3-642-24055-3_15. [CrossRef] [Google Scholar]
  7. L. Yi-bo and L. Jun-jun, “Harris Corner Detection Algorithm Based on Improved Contourlet Transform”, Procedia Eng., vol. 15, pp. 2239–2243, 2011. [Google Scholar]
  8. M. R. Reshma and B. Kannan, “Approaches on Partial Face Recognition: A Literature Review,” in 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, Apr 2019, pp. 538–544. [CrossRef] [Google Scholar]
  9. A. Chater et A. Lasfar, « Comparison of robust methods for extracting descriptors and facial matching », in 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS), Fez, Morocco, avr. 2019, p. 1–4. [Google Scholar]
  10. Junfeng Bai, Yong Ma, Jing Li, Fan Fan, and Hongyuan Wang, “Novel averaging window filter for SIFT in infrared face recognition,” Chin. Opt. Lett., vol. 9, no. 8, pp. 081002–081005, 2011. [CrossRef] [Google Scholar]
  11. S. Gupta, K. Thakur, and M. Kumar, “2D-human face recognition using SIFT and SURF [Google Scholar]
  12. Descriptors of face's feature regions,” Vis. Comput. Comput. 37, no. 3, pp. 447–456, March [Google Scholar]
  13. 2021. [Google Scholar]
  14. D. Hutchison et al., “Adaptive and Generic Corner Detection Based on the Accelerated [Google Scholar]
  15. Segment Test”, in Computer Vision - ECCV 2010, vol. 6312, K. Daniilidis, P. Maragos, and N. Paragios, eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 183–196 [CrossRef] [Google Scholar]
  16. G. Jiang and Y. Cheng, “An LBP-based multi-scale illumination preprocessing method for face recognition,” J. Electron. China, vol. 26, no. 4, pp. 509–516, Jul. 2009. [Google Scholar]
  17. D. Zhou, X. Yang, N. Peng, and Y. Wang, “Improved-LDA based face recognition using both facial global and local information,” Pattern Recognit. Lett. Vol. 27, no. 6, pp. 536–543, Apr. 2006, DOI: 10.1016/j.patrec.2005.09.015. [CrossRef] [Google Scholar]
  18. W. Yang, C. Sun, L. Zhang, and K. Ricanek, “Laplacian bidirectional PCA for face recognition,” Neurocomputing, vol. 74, no. 1-3, pp. 487–493, Dec. 2010. [CrossRef] [Google Scholar]
  19. M. Matsugu, K. Mori, and T. Suzuki, “Face Recognition Using SVM Combined with CNN for Face Detection,” in Neural Information Processing, vol. 3316, N. R. Pal, N. Kasabov, R. K. Mudi, S. Pal, and S. K. Parui, eds. Berlin, Heidelberg: Springer Berlin Heidelberg, [Google Scholar]
  20. 2004, pp. 356–361. [Google Scholar]
  21. S. B. Dabhade et al., “Double Layer PCA based Hyper Spectral Face Recognition using KNN Classifier”, in 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC), Mysore, India, Sep 2017, pp. 289–293. [CrossRef] [Google Scholar]
  22. V. A. D. Hebbar, V. S. Shekhar, K. N. B. Murthy, and S. Natarajan, “Two Novel Detector- Descriptor Based Approaches for Face Recognition Using SIFT and SURF,” Procedia Comput. Sci., vol. 70, pp. 185–197, 2015. [Google Scholar]
  23. A. Chater and A. Lasfar, “New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT, and SURF)”, TELKOMNIKA Telecommun. Comput. Electron. Control, vol. 18, no. 2, p. 695, Apr. 2020. [Google Scholar]
  24. V. A. N. Aklecha, Meghana, K. N. B. Murthy, and S. Natarajan, “On Detectors and Descriptors based Techniques for Face Recognition”, Procedia Comput. Sci. vol. 132, pp. 908–917, 2018. [Google Scholar]
  25. G. Du, F. Su, and A. Cai, “Face recognition using SURF features,” Yichang, China, Oct.2009, pp. 749628. [Google Scholar]
  26. A. Chater, A. Lasfar, and A. Et-Tahir, “Face Recognition Using Feature Extraction and Similarity Measures,” vol. 62, no. 03, p. 10, 2020. [Google Scholar]
  27. P. K B and M. J, “Design and Evaluation of a RealTime Face Recognition System using Convolutional Neural Networks”, Procedia Comput. Sci., vol. 171, pp. 1651–1659, 2020. [Google Scholar]
  28. P. Kamencay, M. Zachariasova, R. Hudec, R. Jarina, M. Benco, and J. Hlubik, “A Novel Approach to Face Recognition using Image Segmentation Based on SPCA-KNN Method,” vol. 22, no. 1, p. 8, 2013. [Google Scholar]
  29. B. Ameur, S. Masmoudi, A. G. Derbel, and A. Ben Hamida, “Fusing Gabor and LBP feature sets for KNN and SRC-based face recognition,” in 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Monastir, Tunisia, March 2016, pp. 453–458. [CrossRef] [Google Scholar]
  30. AT&T Database of Faces 'ORL Face Database' AT&T Laboratories, Cambridge [Google Scholar]
  31. D. B. Graham and N. M. Allinson. In Face recognition: From theory to applications, NATO ASI Series F, Computer and Systems Sciences, 163:446–456. 1998. [Google Scholar]
  32. Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller. Labeled Faces in the wild: a database for studying face recognition in unconstrained environments. University of Massachusetts, Amherst, Technical Report 07-49, October 2007. [Google Scholar]

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