Pipelined minutiae extraction from fingerprint images

Alibeigi, Eman; Rizi, Majid Toghiani; Behnamfar, Parisa

doi:10.1109/ccece.2009.5090128

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…The ridges are thinned and the resulting image is enhanced using an adaptive morphological filter. Square-based method was presented in (Gamassi et al, 2005) and (Alibeigi et al, 2009). The Square-based method is composed of the following steps, repeated for each pixel of the binary image: 1.…”

Section: Ridge Orientation Approachmentioning

confidence: 99%

Minutiae-based Fingerprint Extraction and Recognition

Zaeri¹

2011

Biometrics

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Section: Ridge Orientation Approachmentioning

confidence: 99%

Minutiae-based Fingerprint Extraction and Recognition

Zaeri¹

2011

Biometrics

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“…The state of the art in automatic fingerprint-based authentication systems (AFAS) points out two physical system architectures currently in use: 1) Personal computer platforms [1], [2] based on powerful multicore processors running at high frequencies (1-3 GHz); and 2) Embedded systems based on low-cost microprocessors or digital signal processors (DSPs) [3], [4] running at moderate working frequencies (50-400 MHz), with or without the support of companion chips such as applicationspecific standard products (ASSPs) or application-specific integrated circuits (ASICs) [5], [6] in charge of the acceleration of specific tasks. Moreover, many academic research works deal with the implementation of some of the stages that take place in the recognition algorithm through programmable logic devices such as field-programmable gate arrays (FPGAs) [7], [8] as a more flexible alternative solution to those embedded systems based on fixed hardware resources. Fig.…”

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confidence: 99%

Fingerprint Image Processing Acceleration Through Run-Time Reconfigurable Hardware

Fons

Cantó

2010

IEEE Trans. Circuits Syst. II

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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.

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