Recognizable-image selection for fingerprint recognition with a mobile-device camera

Dongjae Lee, Kyoungtaek Choi, Heeseung Choi, Jaihie Kim

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


This paper proposes a recognizable-image selection algorithm for fingerprint-verification systems that use a camera embedded in a mobile device. A recognizable image is defined as the fingerprint image which includes the characteristics that are sufficiently discriminating an individual from other people. While general camera systems obtain focused images by using various gradient measures to estimate high-frequency components, mobile cameras cannot acquire recognizable images in the same way because the obtained images may not be adequate for fingerprint recognition, even if they are properly focused. A recognizable image has to meet the following two conditions: First, valid region in the recognizable image should be large enough compared with other nonrecognizable images. Here, a valid region is a well-focused part, and ridges in the region are clearly distinguishable from valleys. In order to select valid regions, this paper proposes a new focus-measurement algorithm using the secondary partial derivatives and a quality estimation utilizing the coherence and symmetry of gradient distribution. Second, rolling and pitching degrees of a finger measured from the camera plane should be within some limit for a recognizable image. The position of a core point and the contour of a finger are used to estimate the degrees of rolling and pitching. Experimental results show that our proposed method selects valid regions and estimates the degrees of rolling and pitching properly. In addition, fingerprint-verification performance is improved by detecting the recognizable images.

Original languageEnglish
Pages (from-to)233-243
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number1
Publication statusPublished - 2008 Feb

Bibliographical note

Funding Information:
Manuscript received October 12, 2006; revised April 30, 2007. This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center, Yonsei University, Korea. This paper was recommended by Associate Editor N. Ratha. D. Lee is with the Embedded S/W Center, System LSI, Samsung Electronics Company, Ltd., Gyeonggi-Do 446 711, Korea. K. Choi, H. Choi, and J. Kim are with the Biometrics Engineering Research Center, School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea. Color versions of one or more of the figures in this paper are available online at Digital Object Identifier 10.1109/TSMCB.2007.908869

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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