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Feature Selection for Hand-Shape Based Identification

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International Joint Conference (CISIS 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 369))

Abstract

The shape of a hand contains important information regarding the identity for a person. Hand based identification using high-order Zernike moments is a robust and powerful method. But the computation of high-order Zernike moments is very time-consuming. On the other hand, the number of high-order Zernike moments increases quadratically with order causing storage problem; all of them are not relevant and involve redundancy. To overcome this issue, the solution is to select the most discriminative features that are relevant and not redundant. There exists a lot of feature selection algorithms, different algorithms give good performance for different applications, and to choose the one that is effective for this problem is a matter of investigation. We examined a large number of state-of-the-art feature selection methods and found Fast Correlation-Based Filter (FCBF) and Sparse Bayesian Multinomial Logistic Regression (SBMLR) to be the best methods that are efficient and effective in reducing the dimension of the feature space significantly (by 62 %), i.e. the storage requirements and also slightly enhanced recognition rate (from 99.16 ± 0.44 to 99.42 ± 0.36).

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Acknowledgment

This project was supported by NSTIP strategic technologies programs, grant number 12-INF2582-02 in the Kingdom of Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

    Muhammad Hussain, Awabed Jibreen, Hatim Aboalsmah & Hassan Madkour

  2. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis & Gholamreza Amayeh

Authors
  1. Muhammad Hussain
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  2. Awabed Jibreen
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  3. Hatim Aboalsmah
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  4. Hassan Madkour
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  5. George Bebis
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  6. Gholamreza Amayeh
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Corresponding author

Correspondence to Muhammad Hussain .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, Escuela Politécnica Superior, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. Department of Civil Engineering, Escuela Politécnica Superior, University of Burgos, Burgos, Spain

    Bruno Baruque

  3. Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  4. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  5. Plaza de la Merced S/N, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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© 2015 Springer International Publishing Switzerland

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Hussain, M., Jibreen, A., Aboalsmah, H., Madkour, H., Bebis, G., Amayeh, G. (2015). Feature Selection for Hand-Shape Based Identification. In: Herrero, Á., Baruque, B., Sedano, J., Quintián, H., Corchado, E. (eds) International Joint Conference. CISIS 2015. Advances in Intelligent Systems and Computing, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-319-19713-5_21

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  • DOI: https://doi.org/10.1007/978-3-319-19713-5_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19712-8

  • Online ISBN: 978-3-319-19713-5

  • eBook Packages: EngineeringEngineering (R0)

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