• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.909-921
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• 1995

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the Fast Fourier Transform (FFT) in determining the directions of ridges in fingerprint images, and utilizes statistical information in recognizing the fingerprints. The information used in fingerprint recognition is based on the dircetions along ridge curves and characteristic points such as core points and delta points. In order to find ridge directions, the algorithm applies the FFT to a small block of the size 8x8 pixels, and decides the directions by interpreting the resulted Fourier spectrum. By using the FFT, the algorithm does not require conventional preprocessing procedures such as smoothing, binarization, thinning, and restorationl. Finally, in matching two fingerprint images, the algorithm searches and compares two kinds of feature blocks, one as the blocks where the dircetions cannot be defined from the Fourier spectrum, and the other as the blocks where the changes of directions become abrupt. The proposed algorithm has been implemented on a SunSparc-2 workstation under the Open Window environment. In the experiment, the proposed algorithm has been applied to a set of fingerprint images obtained by a prism system. The result has shown that while the rate of Type II error - Incorrect recognition of two different fingerprints as the identical fingerprints - is held at 0.0%, the rate of Type I error - Incorrect recognition of two identical fingerprints as the different ones - is 2.2%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.247-252
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• 2004

This paper proposes a matching algorithm using Voronoi diagram for rotation and translation invariant fingerprint identification. The proposed algorithm extracts geometrical structures that are derived from Voronoi diagram of a fingerprint image. Then two features, distances and angles are extracted from the geometrical structures and saved as indexing form for fingerprint matching. This matching algerian has a lower error rate than indexing based methods of old times.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.570-574
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• 2010

A thinning algorithm changes a binary fingerprint image to one pixel width. A thinning stage occupies 40% cycle of 32-bit RISC microprocessor system for a fingerprint identification algorithm. Hardware block processing is more effective than software one in speed, because a thinning algorithm is iteration of simple instructions. This paper describes an effective hardware scheme for thinning stage processing using the Verilog-HDL in $160\times192$ Pixel Array. The ZS algorithm was applied for a thinning stage. The hardware scheme was designed and simulated in RTL. The logic was also synthesized by XST in FPGA environment. Experimental results show the performance of the proposed scheme.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.716-720
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• 2010

This paper proposes an effective fingerprint identification system with hardware block for thinning stage processing of a verification algorithm based on minutiae with 39% occupation of 32-bit RISC microprocessor cycle. Each step of a fingerprint algorithm is analyzed based on FPGA and ARMulator. This paper designs an effective hardware scheme for thinning stage processing using the Verilog-HDL in $160{\times}192$ pixel array. The ZS algorithm is applied for a thinning stage. The logic is also synthesized in $0.35{\mu}m$ 4-metal CMOS process. The layout is performed based on an auto placement-routing and post-simulation is performed in logic level. The result is compared with a conventional one.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2816-2822
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• 1999

In this paper, a fast thinning method for fingerprint image by separating end and bifurcation region is proposed. To detect feature points in automatic fingerprint identification system, thinning of fingerprint is essential. The end and bifurcation regions in ridge line are separated by means of run-length coding, and parallel thinning method is applied to the separated regions. The rest parts except the end and bifurcation regions are processed by connecting center points of each run. The performance of the proposed method has been evaluated by CPU processing time and thinness measurement. By the experimental results, the proposed method is fast and has high thinness value.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.852-862
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• 2017

In this work a Discrete Cosine Transform (DCT)-based feature dimensionality reduced approach for fingerprint matching is proposed. The DCT is applied on a small region around the core point of fingerprint image. The performance of our proposed method is evaluated on a small database of Bologna University and two large databases of FVC2000. A dimensionally reduced feature vector is formed using only approximately 19%, 7%, and 6% DCT coefficients for the three databases from Bologna University and FVC2000, respectively. We compared the results of our proposed method with the discrete wavelet transform (DWT) method, the rotated wavelet filters (RWFs) method, and a combination of DWT+RWF and DWT+(HL+LH) subbands of RWF. The proposed method reduces the false acceptance rate from approximately 18% to 4% on DB1 (Database of Bologna University), approximately 29% to 16% on DB2 (FVC2000), and approximately 26% to 17% on DB3 (FVC2000) over the DWT based feature extraction method.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.65-72
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• 2020

In this paper, a USB module with fingerprint recognition was designed as a distributed node of blockchain on distributed ID (DID, distributed ID) for user identification. This biometric-linked fingerprint recognition device was verified for the real-time authentication process of authentication transaction with FIDO(Fast IDentity Online) server. Blockchain DID-based services were proposed like as a method of individual TV rating survey, and recommending service for customized shopping channels, and crypto-currency, too. This DID based remote service can be improved by recognizing of channel-changing information through personal identification. The proposed information of production purchase can be shared by blockchain. And customized service can be provided for the utilization of purchase history in shoppingmall using distributed ID. As a result, this blockchain node-device and Samsung S10 Key-srore with FIDO service can be certified for additional transactions through various biometric authentication like fingerprint, and face recognition.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.959-967
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• 2004

Jain et al. proposed the hybrid matching method which was combined the minutia-based matching method and the filter-bank based matching method. And, their experimental results proved the hybrid matching method was more effective than each of them. However, this hybrid method cannot utilize each peculiar advantage of two methods. The reason is that it gets the matching score by simply summing up each weighted matching score after executing two methods individually. In this paper, we propose new hybrid matching method. It mixes two matching methods during the feature extraction process. This new hybrid method has lower ERR than the filter-bank based method and higher ERR than the minutia-based method. So, we propose the adaptive hybrid scoring method, which selects the matching score in order to preserve the characteristics of two matching methods. Using this method, we can get lower ERR than the hybrid matcher by Jain et al. Experimental results indicate that the proposed methods can improve the matching performance up to about 1% in ERR.

• Analytical Science and Technology
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• v.29 no.3
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• pp.142-153
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• 2016

In crime scene investigation, fingerprint identification is regarded to be one of the most important techniques for personal identification. However, objective and unbiased evaluation methods that would compare the fingerprints with diverse available and developing methods are currently lacking. To develop an objective and quantitative method to improve fingerprint evaluation, a preliminary study was performed to extract useful research information from the analysis with densitometric image analysis (CP Atlas 2.0) and the Automated Fingerprint Identification System (AFIS) for the developed fingerprints on porous surfaces. First, inked fingerprints obtained by varying pressure (kg.f) and pressing time (sec.) to find optimal conditions for obtaining fingerprint samples were analyzed, because they could provide fingerprints of a relatively uniform quality. The extracted number of minutiae from the analysis with AFIS was compared with the calculated areas of friction ridge peaks from the image analysis. Inked fingerprints with a pressing pressure of 1.0 kg.f for 5 seconds provided the most visually clear fingerprints, the highest number of minutiae points, and the largest average area of the peaks of the friction ridge. In addition, the images of the developed latent fingerprints on thermal paper with the iodine fuming method were analyzed. Fingerprinting condition of 1.0 kg.f/5 sec was also found to be optimal when generating highest minutiae number and the largest average area of peaks of ridges. Additionally, when the concentration of ninhydrin solution (0.5 % vs. 5 %) was used to compare the developed latent fingerprints on print paper, the best fingerprinting condition was 2.0 kg.f/5 sec and 5 % of ninhydrin concentration. It was confirmed that the larger the average area of the peaks generated by the image analysis, the higher the number of minutiae points was found. With additional tests for fingerprint evaluation using the densitometric image analysis, this method can prove to be a new quantitative and objective assessment method for fingerprint development.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.870-878
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• 2013

In this paper, we propose a novel fingerprint classification method to enhance the accuracy and efficiency of the fingerprint identification system, one of biometrics systems. According to the previous researches, fingerprints can be categorized into the several patterns based on their pattern of ridges and valleys. After construction of fingerprint database based on their patters, fingerprint classification approach can help to accelerate the fingerprint recognition. The reason is that classification methods reduce the size of the search space to the fingerprints of the same category before matching. First, we suggest a method to extract region of interest (ROI) which have real information about fingerprint from the image. And then we propose a feature extraction method which combines gray level co-occurrence matrix (GLCM) and wavelet features. Finally, we compare the performance of our proposed method with the existing method which use only GLCM as the feature of fingerprint by using the multi-layer perceptron and support vector machine.