GENDER VERIFICATION SYSTEM BASED ON JADE-ICA - Application to Biometric Identification System

Marcos del Pozo, Carlos M. Travieso, Jesús B. Alonso, Miguel A. Ferrer

Abstract

Biometric systems are one of the hottest topics in technology research due their possibilities. An example of these systems may be able to differ between male and female humans. This is called a gender classifier, and it finds applications in areas such as security, marketing, or even as a reinforcement of other biometric systems like face identification. In this work, a gender classifier system is modelled. The system implements two different feature extraction algorithms based on Independent Component Analysis (ICA). On the other hand, Support Vector Machines (SVM) is used as the classifier method. Finally, after 50 runs and 350 independent samples tested in each run, results give rise to an average of 82.40% of success working with Joint Approximate Diagonalization of Eigen-matrices (JADE) ICA and SVM. Moreover, significant differences between JADE-ICA and Fast-ICA algorithms have been pointed out, not only in terms of success rate, but also in stability.

References

  1. Aji, S., Jayanthi, T., Kaimal, M. R., 2009. Gender identification in face images using KPCA. World Congress on Nature & Biologically Inspired Computing, 2009. pp. 1414-1418.
  2. Bau-Cheng S., Chu-Song C., Hui-Huang H., 2009. Fast gender recognition by using a shared-integral-image approach. IEEE International Conference on Acoustics, Speech and Signal Processing, pp.521-524.
  3. Biometric International Group, 2010. Available: http:// www.biometricgroup.com/reports/public/market_repor t.php
  4. Cardoso, J. F., 1999. High-order contrasts for independent component analysis, Neural Computation, 11(1), pp. 157-192
  5. Castrillon-Santana, M., Vuong, Q. C., 2007. An Analysis of Automatic Gender Classification, Lector Notes on Computer Science, Springer, Vol. 4756, pp. 271-280.
  6. Fok, H. C. T., Bouzerdoum, A., 2006. A Gender Recognition System using Shunting Inhibitory Convolutional Neural Networks, International Joint Conference on Neural Networks, pp. 5336-5341.
  7. Hyvärinen, A., Karhunen, J., and Oja, E., 2001. Independent Component Analysis, Editorial WileyInterscience.
  8. Jain, A., Huang, J., 2004. Integrating independent components and linear discriminant analysis for gender classification, Proceedings Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 159-163, 17-19 May 2004
  9. Jain, A., Huang, J., 2004b. Integrating independent components and support vector machines for gender classification, Proceedings of the 17th International Conference on Pattern Recognition, vol.3, pp. 558- 561, 23-26 Aug. 2004
  10. Jing-Ming, G., Chen-Chi, L., Hoang-Son, N., 2010. Face gender recognition using improved appearance-based Average Face Difference and support vector machine, International Conference on System Science and Engineering (ICSSE 2010), pp.637-640.
  11. Prince, S. J. D., Aghajanian, J., 2009. Gender classification in uncontrolled settings using additive logistic models, Processing 16th IEEE International Conference on Image, pp. 2557-2560, 7-10 Nov. 2009
  12. Ramesha, K., Srikanth, N., Raja, K. B., Venugopal, K. R., Patnaik, L. M., 2009. Advanced Biometric Identification on Face, Gender and Age Recognition. International Conference on Advances in Recent Technologies in Communication and Computing, pp.23-27.
  13. Tariq, U., Yuxiao, H., Huang, T. S., 2009. Gender and ethnicity identification from silhouetted face profiles. 16th IEEE International Conference on Image Processing, pp.2441-2444.
  14. Travieso, C. M., Alonso, J. B., Ferrer, M. A., 2004. Facial identification using transformed domain by SVM, in 38th IEEE International Carnahan Conference on security Technology, pp. 321-324.
  15. Xue-Ming, L., Yi-Ding, W., 2008. Gender classification based on fuzzy SVM, International Conference on Machine Learning and Cybernetics, vol.3, pp. 1260- 1264, 12-15 July 2008
  16. Yiding, W., Ning, Z., 2009. Gender Classification Based on Enhanced PCA-SIFT Facial Features, 1st International Conference on Information Science and Engineering, pp. 1262-1265, 26-28 Dec. 2009
  17. Yi-qiong, X., Bi-Cheng, L., Bo, W., 2004. Face Recognition by Fast Independent Component Analysis and Genetic Algorithm, Fourth International Conference on Computer Information Technology, pp. 194-198.
Download


Paper Citation


in Harvard Style

del Pozo M., Travieso C., Alonso J. and Ferrer M. (2011). GENDER VERIFICATION SYSTEM BASED ON JADE-ICA - Application to Biometric Identification System . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: MPBS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 570-576. DOI: 10.5220/0003297605700576


in Bibtex Style

@conference{mpbs11,
author={Marcos del Pozo and Carlos M. Travieso and Jesús B. Alonso and Miguel A. Ferrer},
title={GENDER VERIFICATION SYSTEM BASED ON JADE-ICA - Application to Biometric Identification System},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: MPBS, (BIOSTEC 2011)},
year={2011},
pages={570-576},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003297605700576},
isbn={978-989-8425-35-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: MPBS, (BIOSTEC 2011)
TI - GENDER VERIFICATION SYSTEM BASED ON JADE-ICA - Application to Biometric Identification System
SN - 978-989-8425-35-5
AU - del Pozo M.
AU - Travieso C.
AU - Alonso J.
AU - Ferrer M.
PY - 2011
SP - 570
EP - 576
DO - 10.5220/0003297605700576