Conference Paper

A digital circuit for extracting singular points from fingerprint images

DOI: 10.1109/ICECS.2011.6122353 Conference: 18th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2011, Beirut, Lebanon, December 11-14, 2011
Source: DBLP


Since singular point extraction plays an important role in many fingerprint recognition systems, a digital circuit to implement such processing is presented herein. A novel algorithm that combines hardware efficiency with precision in the extraction of the points has been developed. The circuit architecture contains three main building blocks to carry out the three main stages of the algorithm: extraction of a partitioned directional image, smoothing, and searching for the patterns associated with singular points. The circuit processes the pixels in a serial way, following a pipeline scheme and executing in parallel several operations. The design flow employed has been supported by CAD tools. It starts with high-level descriptions and ends with the hardware prototyping into a FPGA from Xilinx.

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    • "They are embedded in many commercial systems, such as some laptops and mobile phones. The embedded systems usually use low cost hardware digital modules such as FPGA [1] [2] or DSP [3]. Fingerprint authentication systems are also used in many airport countries worldwide. "
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    ABSTRACT: The core point is used to align between the fingerprints in the fingerprint authentication systems faster than the conventional techniques. To speed up the processing for the real time applications, it is more convenient to implement the image processing algorithms using embedded modules that can be used in the portable systems. To do this, the algorithm should be characterized by a simple design for easier and more feasible implementation on the embedded modules. The proposed work, in this paper, presents a mask that locates the core point simply from the ridge orientation map. The introduced algorithm detects the core point at the end of the discontinuous line appearing in the orientation map presented by a gray-scale. A property is presented and supported with a mathematical proof to verify that the singular regions are located at the end of this discontinuous line. The experimental results, on the public FVC2002 and FVC2004 databases, show that the proposed mask exhibits an average increase in the correct core point detection per fingerprint by 17.35%, with a reduction in the false detection by 51.23%, compared to a fast edge-map based method. Moreover, the execution time is reduced by an average factor of 1.8.
    Full-text · Article · Mar 2013 · Egyptian Informatics Journal
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    ABSTRACT: Most of contributions for biometric recognition solutions (and specifically for fingerprint recognition) are implemented in software on PC or similar platforms. However, the wide spread of embedded systems means that fingerprint embedded systems will be progressively demanded and, hence, hardware dedicated solutions are needed to satisfy their constraints. CAD tools from Matlab-Simulink ease hardware design for embedded systems because automatize the design process from high-level descriptions to device implementation. Verification of results is set at different abstraction levels (high-level description, hardware code simulation, and device implementation). This paper shows how a design flow based on models facilitates the selection of algorithms for fingerprint embedded systems. In particular, the search of a solution for directional image extraction suitable for its application to singular point extraction is detailed. Implementation results in terms of area occupation and timing are presented for different Xilinx FPGAs.
    No preview · Conference Paper · Dec 2012
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    ABSTRACT: Biometric recognition systems are rapidly evolving technologies and their use in embedded devices for accessing and managing data and resources is a very challenging issue. Usually, they are composed of three main modules: Acquisition, Features Extraction and Matching. In this paper the hardware design and implementation of an efficient fingerprint features extractor for embedded devices is described. The proposed architecture, designed for different acquisition sensors, is composed of four blocks: Image Pre-processor, Macro-Features Extractor, Micro- Features Extractor and Master Controller. The Image Pre- processor block increases the quality level of the input raw image and performs an adaptive binarization, introducing a novel hardware approach. The Macro-Features Extractor extracts singularity points. The Micro-Features Extractor extracts only micro-features around singularity points using an adaptive thinning and a post-processing phase to remove potential false micro-features. The Master Controller synchronizes and coordinates the two extractors. Xilinx ML507 board has been used to develop the prototype, while tests have been conducted on the PolyU (Hong Kong Polytechnic University) and the FVC2002 DB2-B free databases. These two databases have been chosen for their different characteristics in terms of image resolution and dimension in order to test the effectiveness of the proposed architecture. Experimental results show an interesting trade-off between used resources (about 32%) and fingerprint features extraction time (the lower execution time is 21.6 ms while the higher execution time is 28.4 ms, with a working frequency of 25 MHz), obtaining the best rate of false minutiae discharged of 5%.
    No preview · Conference Paper · Aug 2014