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A review of wavelet transform based techniques for denoising latent fingerprint images

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dc.contributor.author Mgaga, Sboniso S
dc.contributor.author Khanyile, Nontokozo P
dc.contributor.author Tapamo, J
dc.date.accessioned 2020-12-03T11:29:12Z
dc.date.available 2020-12-03T11:29:12Z
dc.date.issued 2019-10
dc.identifier.citation Mgaga, S.S., Khanyile, N.P. & Tapamo, J. 2019. A review of wavelet transform based techniques for denoising latent fingerprint images. In: Open Innovations Conference (OI), Cape Peninsula University of Technology, South Africa, 2-4 October 2019 en_US
dc.identifier.isbn 978-1-7281-3464-2
dc.identifier.isbn 978-1-7281-3463-5
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/8908252
dc.identifier.uri DOI: 10.1109/OI.2019.8908252
dc.identifier.uri https://ieeexplore.ieee.org/xpl/conhome/8897709/proceeding
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8908215
dc.identifier.uri http://hdl.handle.net/10204/11686
dc.description Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Open Innovations Conference (OI), Cape Peninsula University of Technology, South Africa, 2-4 October 2019 en_US
dc.description.abstract Authentication systems robustness can be affected by the fingerprint image quality. Fingerprint image denoising is essential for better performance of any authentication system. In this paper, most recent wavelet transform based techniques for fingerprint image denoising are reviewed. It is observed that there are four important components of wavelet transform based denoising techniques. These important components include wavelet filter, thresholding rule, threshold value computation method and the level of decomposition. The stationary wavelet transform and the weighted median are recommended over conventional discrete wavelet transform and median estimator. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Workflow;23285
dc.subject Biometrics en_US
dc.subject Denoising en_US
dc.subject Fingerprints en_US
dc.subject Threshold en_US
dc.subject Wavelets en_US
dc.title A review of wavelet transform based techniques for denoising latent fingerprint images en_US
dc.type Article en_US
dc.identifier.apacitation Mgaga, S. S., Khanyile, N. P., & Tapamo, J. (2019). A review of wavelet transform based techniques for denoising latent fingerprint images. http://hdl.handle.net/10204/11686 en_ZA
dc.identifier.chicagocitation Mgaga, Sboniso S, Nontokozo P Khanyile, and J Tapamo "A review of wavelet transform based techniques for denoising latent fingerprint images." (2019) http://hdl.handle.net/10204/11686 en_ZA
dc.identifier.vancouvercitation Mgaga SS, Khanyile NP, Tapamo J. A review of wavelet transform based techniques for denoising latent fingerprint images. 2019; http://hdl.handle.net/10204/11686. en_ZA
dc.identifier.ris TY - Article AU - Mgaga, Sboniso S AU - Khanyile, Nontokozo P AU - Tapamo, J AB - Authentication systems robustness can be affected by the fingerprint image quality. Fingerprint image denoising is essential for better performance of any authentication system. In this paper, most recent wavelet transform based techniques for fingerprint image denoising are reviewed. It is observed that there are four important components of wavelet transform based denoising techniques. These important components include wavelet filter, thresholding rule, threshold value computation method and the level of decomposition. The stationary wavelet transform and the weighted median are recommended over conventional discrete wavelet transform and median estimator. DA - 2019-10 DB - ResearchSpace DP - CSIR KW - Biometrics KW - Denoising KW - Fingerprints KW - Threshold KW - Wavelets LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-3464-2 SM - 978-1-7281-3463-5 T1 - A review of wavelet transform based techniques for denoising latent fingerprint images TI - A review of wavelet transform based techniques for denoising latent fingerprint images UR - http://hdl.handle.net/10204/11686 ER - en_ZA


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