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SVM Based Adaptive Biometric Image Enhancement Using Quality Assessment

  • Chapter
Speech, Audio, Image and Biomedical Signal Processing using Neural Networks

Part of the book series: Studies in Computational Intelligence ((SCI,volume 83))

The quality of input data has an important role in the performance of a biometric system. Images such as fingerprint and face captured under non-ideal conditions may require additional preprocessing. This chapter presents intelligent SVM techniques for quality assessment and enhancement. The proposed quality assessment algorithm associates the quantitative quality score of the image that has a specific type of irregularity such as noise, blur, and illumination. This enables the application of the most appropriate quality enhancement algorithm on the non-ideal image. We further propose a SVM quality enhancement algorithm which simultaneously applies selected enhancement algorithms to the original image and selects the best quality regions from the global enhanced image. These selected regions are used to generate single high quality image. The performance of the proposed algorithms is validated by considering face biometrics as the case study. Results show that the proposed algorithms improve the verification accuracy of face recognition by around 10–17%.

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Author information

Authors and Affiliations

  1. West Virginia University, Morgantown, WA, USA

    Mayank Vatsa, Richa Singh & Afzel Noore

Authors
  1. Mayank Vatsa
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  2. Richa Singh
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  3. Afzel Noore
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307, USA

    Bhanu Prasad

  2. Department of Electronics and Communication Engineering, Indian Institute of Technology Guwahati, Guwahati, India

    S. R. Mahadeva Prasanna

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© 2008 Springer-Verlag Berlin Heidelberg

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Vatsa, M., Singh, R., Noore, A. (2008). SVM Based Adaptive Biometric Image Enhancement Using Quality Assessment. In: Prasad, B., Prasanna, S.R.M. (eds) Speech, Audio, Image and Biomedical Signal Processing using Neural Networks. Studies in Computational Intelligence, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75398-8_16

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  • DOI: https://doi.org/10.1007/978-3-540-75398-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75397-1

  • Online ISBN: 978-3-540-75398-8

  • eBook Packages: EngineeringEngineering (R0)

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