Fingerprint verification using ridge direction distribution and minutiae correspondence

Wakahara, Toru; Kimura, Yoshimasa; Suzuki, Akira; Shio, Akio; Sano, Mutsuo

doi:10.1002/scj.10522

Cited by 3 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The usual method of evaluating the accuracy of the fingerprint verification algorithm is to use the ROC (receiver operating characteristic) curve, which represents the relation between the rejection rate for the right person (false rejection rate, FRR) and the acceptance rate for other persons (false acceptance rate, FAR) [4,19,20]. In .9)], however, the verification accuracy is lower than in (b).…”

Section: Search For Optimal Value By Matching Experimentsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of low‐quality images and imaging enhancement methods for fingerprint verification

Takeuchi¹,

Umezaki

Matsumoto³

et al. 2007

Electron Comm Jpn Pt III

View full text Add to dashboard Cite

SUMMARYA serious problem of fingerprint verification devices which are easily available on the market is how to handle "dry fingers," which make the reading of fingerprints difficult and often result in incorrect verification. Dry fingers are frequently observed in the elderly and in housewives who are frequently engaged in wet work. In these cases, the observed fingerprint tends to become an eroded fingerprint image, with disconnected ridges. This paper proposes a method of handling eroded fingerprint images in which such images that will result in incorrect verification are automatically identified and the ridges are recovered rapidly. First, a method for image quality evaluation that consists of evaluating the noise in the fingerprint image is discussed and the effectiveness of the method is demonstrated. Then, simple ridge recovery is performed by using edge emphasis for images which are automatically judged to be eroded fingerprints. In the experiment, a fingerprint database was acquired in winter, when dry fingers are common. The acceptance rate for the right person (recognition rate) is found to be 94.8% when the rejection rate for other persons is set as 99.99%. When the ridges are recovered in fingerprint images whose quality is judged to be low by the image evaluation measure proposed in this paper, the recognition rate is improved to 96.2%. Furthermore, when tolerance to dry fingers is considered and verification is not performed for low-quality image judged to be difficult to recover, the recognition rate is improved to 97.2%. In environments in which few users have dry fingers, the recognition rate will be improved to 98.8% when the rejection rate for other persons is set as 99.

show abstract

Section: Search For Optimal Value By Matching Experimentsmentioning

confidence: 99%

“…In addition, fingerprint verification can be realized by relatively cheap devices. Consequently, there have been intensive studies of personal identification using fingerprints [2][3][4][5][6][7][8][9][10][11][12][13][14]. Recently, as third-generation keys, many companies are offering fingerprint verification devices on the market.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of low‐quality images and imaging enhancement methods for fingerprint verification

Takeuchi¹,

Umezaki

Matsumoto³

et al. 2007

Electron Comm Jpn Pt III

View full text Add to dashboard Cite

show abstract

“…All those processing steps are abstracted from [10]. Next, the fingerprint alignment stage is abstracted from [11], where a correlation analysis of template and query field orientation maps is performed in order to find the best overlapped area between both fingerprints. If a valid alignment is found, the next stage consists of matching the previously aligned feature sets.…”

mentioning

confidence: 99%

Fingerprint Image Processing Acceleration Through Run-Time Reconfigurable Hardware

Fons

Cantó

2010

IEEE Trans. Circuits Syst. II

View full text Add to dashboard Cite

Abstract-To the best of the authors' knowledge, this is the first brief that implements a complete automatic fingerprint-based authentication system (AFAS) application under a dynamically partial self-reconfigurable field-programmable gate array (FPGA). The main benefits of this implementation are the acceleration of the processing reached by the parallelism inherent to the hardware design, the high level of integration, the consequent security and reliability improvements provided by the usage of a system-on-programmable-chip device that is able to embed the main components of the application in a single chip, and the low cost achieved by the whole system due to the reconfigurability performance featured by the suggested FPGA. All these factors result in an outstanding system that is able to authenticate the identity of any user by means of those distinctive characteristics available in fingerprints. This brief reveals the advantages of run-time reconfigurable hardware in the implementation of those embedded systems demanding real-time performance at low cost. The minimization of the reconfiguration overhead by means of the proper sizing of the reconfigurable region in the FPGA and the design of a hardware configuration controller that is able to reach the maximum configuration rates allowed by the technology (3.2 Gb/s) are key factors to succeed in the development of the embedded AFAS application. The proposed system, which is implemented by means of hardware-software co-design techniques under a Virtex4 XC4VLX25 FPGA working at 100 MHz, is able to overcome in one order of magnitude the execution time performance achieved by a personal computer platform based on an Intel Core2Duo microprocessor running at 1.83 GHz. IndexTerms-Biometrics, embedded system, fieldprogrammable gate array (FPGA), fingerprints, flexible hardware, hardware-software co-design, image processing, run-time reconfigurable computing.

show abstract

Real-time embedded systems powered by FPGA dynamic partial self-reconfiguration: a case study oriented to biometric recognition applications

Fons

Cantó

et al. 2011

J Real-Time Image Proc

View full text Add to dashboard Cite

This work aims to pave the way for an efficient open system architecture applied to embedded electronic applications to manage the processing of computationally complex algorithms at real-time and low-cost. The target is to define a standard architecture able to enhance the performance-cost trade-off delivered by other alternatives nowadays in the market like general-purpose multi-core processors. Our approach, sustained by hardware/software (HW/SW) co-design and run-time reconfigurable computing, is synthesizable in SRAM-based programmable logic. As proof-of-concept, a run-time partially reconfigurable field-programmable gate array (FPGA) is addressed to carry out a specific application of high-demanding computational power such as an automatic fingerprint authentication system (AFAS). Biometric personal recognition is a good example of compute-intensive algorithm composed of a series of image processing tasks executed in a sequential order. In our pioneer conception, these tasks are partitioned and synthesized first in a series of coprocessors that are then instantiated and executed multiplexed in time on a partially reconfigurable region of the FPGA. The implementation benchmark of the AFAS either as a pure software approach on a PC platform under a dual-core processor (Intel Core 2 Duo T5600 at 1.83 GHz) or as a reconfigurable FPGA co-design (identical algorithm partitioned in HW/SW tasks operating at 50 or 100 MHz on the second smallest device of the Xilinx Virtex-4 LX family) highlights a speed-up of one order of magnitude in favor of the FPGA alternative. These results let point out biometric recognition as a sensible killer application for run-time reconfigurable computing, mainly in terms of efficiently balancing computational power, functional flexibility and cost. Such features, reached through partial reconfiguration, are easily portable today to a broad range of embedded applications with identical system architecture.Peer ReviewedPostprint (published version

show abstract

Fingerprint verification using ridge direction distribution and minutiae correspondence

Cited by 3 publications

References 7 publications

Evaluation of low‐quality images and imaging enhancement methods for fingerprint verification

Evaluation of low‐quality images and imaging enhancement methods for fingerprint verification

Fingerprint Image Processing Acceleration Through Run-Time Reconfigurable Hardware

Real-time embedded systems powered by FPGA dynamic partial self-reconfiguration: a case study oriented to biometric recognition applications

Contact Info

Product

Resources

About