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Impact of digital fingerprint image quality on the fingerprint recognition accuracy

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Abstract

Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.

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Notes

  1. http://students.iitk.ac.in/projects/roboticsclub_fingerprint

  2. http://www.secugen.com/products/ph4.htm

  3. http://www.accu-time.com/ats-biometric-devices/fingerprint-scanner-types/

  4. https://www.qualcomm.com/products/snapdragon/security/sense-id

  5. http://api.256file.com/freeimage.dll/en-download-77473.html

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Acknowledgments

This work is supported by the Jordan University of Science and Technology Deanship of Research project number 20150348.

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Authors and Affiliations

  1. Computer Science Department, Jordan University of Science and Technology, Irbid, 22110, Jordan

    Mohammad A. Alsmirat, Fatimah Al-Alem, Mahmoud Al-Ayyoub & Yaser Jararweh

  2. National Institute of Technology Kurukshetra, Kurukshetra, India

    Brij Gupta

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  1. Mohammad A. Alsmirat
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Correspondence to Mohammad A. Alsmirat.

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Alsmirat, M.A., Al-Alem, F., Al-Ayyoub, M. et al. Impact of digital fingerprint image quality on the fingerprint recognition accuracy. Multimed Tools Appl 78, 3649–3688 (2019). https://doi.org/10.1007/s11042-017-5537-5

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