Conference Paper

ATM terminal design is based on fingerprint recognition

Sch. of Electr. & Inf. Eng., Shaanxi Univ. of Sci. & Technol., Xi'an, China
DOI: 10.1109/ICCET.2010.5486288 Conference: Computer Engineering and Technology (ICCET), 2010 2nd International Conference on, Volume: 1
Source: IEEE Xplore

ABSTRACT For the traditional ATM terminal customer recognition systems only rely on bank cards, passwords, and such identity verification methods which measures are not perfect and functions are too single. For solving the bugs of traditional ones, the author designs a new ATM terminal customer recognition systems. The chip of S3C2440 is used for the core of microprocessor in ARM9, furthermore, an improved enhancement algorithm of fingerprint image increase the security that customer use the ATM machine.

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    ABSTRACT: Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we develop a fingerprint image enhancement algorithm based on orientation fields; According to the principles of Jain et al.’s matching algorithm, we also introduce ideas along the following three aspects: introduction of ridge information into the minutiae matching process in a simple but effective way, which solves the problem of reference point pair selection with low computational cost; use of a variable sized bounding box to make our algorithm more robust to non-linear deformation between fingerprint images; use of a simpler alignment method in our algorithm. Experiments using the Fingerprint Verification Competition 2000 (FVC2000) databases with the FVC2000 performance evaluation show that these ideas are effective.
    Pattern Recognition Letters 06/2003; 24(9-10-24):1349-1360. DOI:10.1016/S0167-8655(02)00376-8 · 1.06 Impact Factor
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    ABSTRACT: Fingerprint enhancement is a critical step in automatic fingerprint verification system. Most of the existing enhancement uses a set of contextual filters to enhance fingerprint. The main drawback of these methods is these contextual filters based on the local information of the fingerprint, such as ridge width, orientation, curvature etc. This information is unreliable in the areas corrupted by the noise. This paper introduces the scale space theory in the computer vision to enhance the fingerprint. In the enhancement process, decompose fingerprint into a series of images and organize the images by courser to finer scheme. Thus a globe and integrate interpretation is available and it enables us to get rid of the influence of noise to the largest extent. Experiments show our algorithm is fast and improve the performance of fingerprint verification system. � 2004 Elsevier B.V. All rights reserved.
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    ABSTRACT: The "registration pattern" between two fingerprints is the optimal registration of each part of one fingerprint with respect to the other fingerprint. Registration patterns generated from imposter's matching attempts are different from those patterns from genuine matching attempts, although they may share some similarities in the aspect of minutiae. This paper presents an algorithm that utilizes minutiae, associate ridges and orientation fields to determine the registration pattern between two fingerprints and their similarity. The proposed matching scheme has two stages. An offline training stage derives a genuine registration pattern base from a set of genuine matching attempts. Then, an online matching stage registers the two fingerprints and determines the registration pattern. Only if the pattern makes a genuine one, a further fine matching is conducted. The genuine registration pattern base is derived using a set of fingerprints extracted from the NIST Special Database 24. Experimental results on the second FVC2002 database demonstrate the performance of the proposed algorithm.
    Journal of Software 01/2005; 16(6). DOI:10.1360/jos161046

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