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Proceedings ArticleDOI

DSP hardware design for fingerprint binarization and thinning on FPGA

TL;DR: An efficient design of DSP hardware for binarization and thinning of fingerprint images has been achieved based on Otsu's thresholding method for binARization and Zhang and Suen's method for thinning.
Abstract: Binarization and thinning are the two critical preprocessing stages designed for accurate extraction of minutiae features from the preprocessed image in fingerprint identification system. In this work an efficient design of DSP hardware for binarization and thinning of fingerprint images has been achieved based on Otsu's thresholding method for binarization and Zhang and Suen's method for thinning. Optimization has been achieved in our proposed hardware design, which improved the performance in terms of execution speed. The algorithms are designed in Xilinx System Generator using DSP hardware blocks and executed on Xilinx Spartan 6 FPGA (field programmable gate array) device.
Citations
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Proceedings ArticleDOI
01 May 2017
TL;DR: Offered of the perfected wave tracing algorithm is to use a spherical wave on the combined raster image while creating skeleton, to avoid skeletezation of connection segments.
Abstract: Vectorization is happened by a wave method. The wave method is to analyze the path of the way to the spherical wave in the image. At every step is analyzed offset center of point's mass forming a new step wave relative to the previous position of the center of mass. Offered of the perfected wave tracing algorithm is to use a spherical wave on the combined raster image while creating skeleton. The feature of skeletezationon prints, where deposited security elements in the form guilloche, is that almost no curves intersect. This avoids skeletezation of connection segments.

19 citations


Cites background from "DSP hardware design for fingerprint..."

  • ...During the recognition of the fingerprints structure of the figure is a complex shapes (papillary lines of fingers) and wave propagation and its subsequent analysis is of major errors [5]....

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Journal ArticleDOI
17 Jun 2021-Sensors
TL;DR: In this article, a high-throughput implementation of the Otsu automatic image thresholding algorithm on Field Programmable Gate Array (FPGA) aiming to process high-resolution images in real-time was proposed.
Abstract: This work proposes a high-throughput implementation of the Otsu automatic image thresholding algorithm on Field Programmable Gate Array (FPGA), aiming to process high-resolution images in real-time. The Otsu method is a widely used global thresholding algorithm to define an optimal threshold between two classes. However, this technique has a high computational cost, making it difficult to use in real-time applications. Thus, this paper proposes a hardware design exploiting parallelization to optimize the system's processing time. The implementation details and an analysis of the synthesis results concerning the hardware area occupation, throughput, and dynamic power consumption, are presented. Results have shown that the proposed hardware achieved a high speedup compared to similar works in the literature.

10 citations

Patent
10 Aug 2016
TL;DR: In this paper, an image binaryzation target segmentation device and method is presented, which consists of a programmable logic device, a signal processor and a histogram statistic device.
Abstract: The present invention relates to an image binaryzation target segmentation device and method. The device comprises a programmable logic device, a signal processor and a histogram statistic device. The programmable logic device is configured to generate interrupt signals for controlling a digital signal processor and perform background suppression line by line and black-white object segmentation of the real-time video data to output a binary object according to the line gray average value and a black and white object threshold inputted by the digital signal processer; the digital signal processer is configured to read video gray data in the line scanning period according to the interrupt signals and calculate the line gray average value; the histogram gray distribution data is read from the histogram statistic device and the object threshold is calculated; and the histogram statistic device is configured to perform histogram statistics of the real-time video data after background suppression with the pixel clock speed in a real-time scanning format by taking a frame as a unit. The image binaryzation target segmentation device and method are able to realize the binaryzation adaptive segmentation of the object state changing to allow the shape of the segmented object to be more completed.

1 citations

Journal ArticleDOI
TL;DR: This study highlights the performance of the Texas Instrument DSP for processing a biometric fingerprint recognition system.
Abstract: In the context of emerging technologies, Cloud Computing (CC) was introduced as a new paradigm to host and deliver Information Technology Services. Cloud computing is a new model for delivering resources. However, there are many critical problems appeared with cloud computing, such as data privacy, security, and reliability, etc. But security is the most important between these problems. Biometric identification is a reliable and one of the easiest ways to recognize a person using extractable characteristics. In addition, a biometric application requires a fast and powerful processing systems, hence the increased use of embedded systems in biometric applications especially in image processing. Embedded systems have a wide variety and the choice of a well-designed processor is one of the most important factors that directly affect the overall performance of the system. This study highlights the performance of the Texas Instrument DSP for processing a biometric fingerprint recognition system.
Proceedings ArticleDOI
29 Apr 2021
TL;DR: This work proposes an implementation in Field Programmable Gate Array (FPGA) of the Otsu’s method applied to real-time tracking of worms called Caenorhabditis elegans and shows it was possible to achieve a speedup up to 5 times higher than similar works in the literature.
Abstract: This work proposes an implementation in Field Programmable Gate Array (FPGA) of the Otsu’s method applied to real-time tracking of worms called Caenorhabditis elegans. Real-time tracking is necessary to measure changes in the worm’s behavior in response to treatment with Ribonucleic Acid (RNA) interference. Otsu’s method is a global thresholding algorithm used to define an optimal threshold between two classes. However, this technique in real-time applications associated with the processing of high-resolution videos has a high computational cost because of the massive amount of data generated. Otsu’s algorithm needs to identify the worms in each frame captured by a high-resolution camera in a real-time analysis of the worm’s behavior. Thus, this work proposes a highperformance implementation of Otsu’s algorithm in FPGA. The results show it was possible to achieve a speedup up to 5 times higher than similar works in the literature.

Cites background from "DSP hardware design for fingerprint..."

  • ...Um projeto de hardware para binarização e afinamento de imagens de impressões digitais, utilizando o método de Otsu para a binarização, é proposto em [20]....

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  • ...O trabalho apresentado por [20] usou um dispositivo FPGA Xilinx Spartan 6 LX45 e teve uma ocupação de hardware de cerca de 1859 LUTs e 44 blocos de RAM....

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  • ...[20] 280 × 265 10,00 671,59 1351,35 ≈ 2, 01× [18] 1280 × 1024 8,72 43,72 87,49 ≈ 2, 00× [19] 640 × 480 39,72 16,39 81,97 ≈ 5, 00×...

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  • ...[20] apresenta resultados do tempo de execução empregando um clock de 10 ns e uma imagem de entrada com dimensões de 280 × 265, com representação dos pixels usando 8 bits....

    [...]

References
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Journal ArticleDOI

37,017 citations


"DSP hardware design for fingerprint..." refers methods in this paper

  • ...Introduction In computer VISIon and image processing, Otsus global thresholding method [7] is used to perform histogram based image thresholding, which reduces a grayscale image into a binary image....

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Journal ArticleDOI
TL;DR: A fast parallel thinning algorithm that consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other one is aimed at deletion thenorth-west boundarypoints and theSouth-east corner points.
Abstract: A fast parallel thinning algorithm is proposed in this paper It consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other one is aimed at deleting the north-west boundary points and the south-east corner points End points and pixel connectivity are preserved Each pattern is thinned down to a skeleton of unitary thickness Experimental results show that this method is very effective 12 references

2,243 citations

Journal ArticleDOI
TL;DR: A fast fingerprint enhancement algorithm is presented, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency.
Abstract: In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.

2,212 citations

Journal ArticleDOI
TL;DR: This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications, and validates the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery.
Abstract: This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee (1980, 1981, 1986) and Frost (1982) filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.

1,816 citations

Journal ArticleDOI
TL;DR: This work introduces a new approach to automatic fingerprint classification in which the directional image is partitioned into "homogeneous" connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification.
Abstract: In this work, we introduce a new approach to automatic fingerprint classification. The directional image is partitioned into "homogeneous" connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification. A set of dynamic masks, together with an optimization criterion, are used to guide the partitioning. The adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point, which can be conceived as a continuous classification. Different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification. Experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature: As to fingerprint retrieval based on continuous classification, our method gives the best performance and exhibits a very high robustness.

361 citations