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Face recognition using DCT coefficients selection

Published: 16 March 2008 Publication History

Abstract

This paper presents a face recognition method based on Discrete Cosine Transform (DCT) coefficient's selection. Without a normalization phase, the proposed method uses, in its feature selection stage, a technique based only on the DCT coefficients amplitudes. Three coefficient selection criterions were analyzed: the first one is the average of the coefficients' amplitudes; the second one is based on counting the occurrence of each coefficient, which are stored in a set of lists containing the most significant coefficients; finally, the third criterion is based on the average position of the coefficients in a list of coefficients ordered by amplitude. Experimental tests on the ORL Face Database [1] achieved 99.00% of recognition accuracy using only 50 DCT coefficients, with low computational cost. Additionally, the method achieved 100.00% of recognition accuracy when the correct face is within a range of eight returned faces.

References

[1]
AT&T Laboratories, Cambridge, UK. "The ORL Database of Faces" (now AT&T "The Database of Faces"). Available {Online}: http://www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/att_faces.zip {15/September/2007}.
[2]
Batista, L. V., Carvalho, L. C. and Melcher, E. U. K. Compression of ECG Signals Base on Optimum Quantization of Discrete Cosine Transform Coefficients and Golomb-Rice Coding. In Proceeding of the 25th Annual International Conference on the IEEE EMBS. Mexico, Sep. 17--21, 2003.
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Bicego, M., Castellani, U. and Murino V. Using HMM and Wavelets for Face Recognition. Proceedings of the 12th International Conference on Image Analysis and Processing. 2003 IEEE.
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Chai, Douglas and Wong, Kok Wai. Facial Image Processing: An Overview. Proceeding of the 2004 IEEE Conference on Cybernetics and Intelligent Systems, p. 307--311. Singapore, 1--3 December, 2004.
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Duda, R. O.; Hart, P. E. and Stork, D. G. Pattern Classification. Second Edition. Wiley-Interscience. 2000.
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Fáundez-Zanuy, Marcos. Face Recognition in a Transformed Domain. In Proceedings of IEEE 37th Annual 2003 International Carnahan Conference on Security Technology, 2003, p. 290--297.
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Hafed, Ziad M and Levine, Marin D. Face Recognition Using Discrete Cosine Transform. International Journal of Computer Vision, v. 43(3), p. 167--188. 2001.
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Haykin, Simon. Redes Neurais - Princípios e práticas. Tradução de 2a Edição. Bookman. 2001.
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Ivancevic, V.; Kaine, A. K.; McLindin, B. A. and Sunde, J. Factor Analysis of Essencial Facial Features. 25th Int. Conf. Information Technology Interface ITI 2003, p. 187--191. June 16--19, Croatia. 2003.
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Podilchuk, C. and Zhang, X. 1996. Face recognition using DCT-based feature vectors. In Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE international Conference - Volume 04 (May 07 - 10, 1996). ICASSP. IEEE Computer Society, Washington, DC, 2144--2147.
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Rao, K. R. and Yip, P. Discrete Cosine Transform: Algorithms, Advantages, Applications. Academic Press, Inc. 1990.
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Samra, Ahmed Shabann; Allah, Salah. E. T. G and Ibrahim, Rehab Mahmound. Face Recognition Using Wavelet Transform, Fast Fourier Transform and Discrete Cosine Transform. In Proceedings of the 46th IEEE International Midwest Symposium on Circuits and Systems, 2003 {MWSCAS '03}, v. 1, p. 272--275.
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Zhao, W.; Chellappa, R.; Phillips, P. J. and Rosenfeld, A. Face Recognition: A Literature Survey. ACM Computing Surveys, v. 35, n. 4, p. 399--458, 2003.

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  • (2018)Emerging ChallengesRecent Advances in Ensembles for Feature Selection10.1007/978-3-319-90080-3_10(173-205)Online publication date: 1-May-2018
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cover image ACM Conferences
SAC '08: Proceedings of the 2008 ACM symposium on Applied computing
March 2008
2586 pages
ISBN:9781595937537
DOI:10.1145/1363686
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 16 March 2008

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Author Tags

  1. classification
  2. discrete cosine transform
  3. face recognition
  4. feature selection
  5. performance

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SAC '08
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SAC '08: The 2008 ACM Symposium on Applied Computing
March 16 - 20, 2008
Fortaleza, Ceara, Brazil

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2022)A Comprehensive Survey on the Process, Methods, Evaluation, and Challenges of Feature SelectionIEEE Access10.1109/ACCESS.2022.320561810(99595-99632)Online publication date: 2022
  • (2018)Smart Cup to Monitor Stroke Patients Activities During Everyday Life2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)10.1109/Cybermatics_2018.2018.00062(189-195)Online publication date: Jul-2018
  • (2018)Emerging ChallengesRecent Advances in Ensembles for Feature Selection10.1007/978-3-319-90080-3_10(173-205)Online publication date: 1-May-2018
  • (2017)Hybrid BFO and PSO Swarm Intelligence Approach for Biometric Feature OptimizationNature-Inspired Computing10.4018/978-1-5225-0788-8.ch057(1490-1518)Online publication date: 2017
  • (2017)Normalization Methods Analysis Applied to Face Recognition2017 Workshop of Computer Vision (WVC)10.1109/WVC.2017.00026(108-113)Online publication date: Oct-2017
  • (2015)Combining Fisher locality preserving projections and passband DCT for efficient palmprint recognitionNeurocomputing10.1016/j.neucom.2014.11.005152:C(179-189)Online publication date: 25-Mar-2015
  • (2015)Recent advances and emerging challenges of feature selection in the context of big dataKnowledge-Based Systems10.1016/j.knosys.2015.05.01486:C(33-45)Online publication date: 1-Sep-2015
  • (2013)Up-to-Date Feature Selection Methods for Scalable and Efficient Machine LearningEfficiency and Scalability Methods for Computational Intellect10.4018/978-1-4666-3942-3.ch001(1-26)Online publication date: 2013
  • (2012)Circular sector DCT based feature extraction for enhanced face recognition using histogram based dynamic gamma intensity correctionProceedings of the CUBE International Information Technology Conference10.1145/2381716.2381732(74-81)Online publication date: 3-Sep-2012
  • (2012)Spatial domain entropy based local feature extraction scheme for face recognition2012 7th International Conference on Electrical and Computer Engineering10.1109/ICECE.2012.6471475(24-27)Online publication date: Dec-2012
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