• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.861-864
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• 2009

Recently, the biometric recognition technology of veins in different parts of hand is very active. In this paper the image hierarchical slicing provides a way to detect vein patterns. The scanned vein image will be sliced into various thicknesses. We first get the average brightness values of the sliced image and then convert them into curvature where we can detect candidates of the vein. The candidates of the vein are used to do a further analysis. We search all of the vein candidates and analyze them to get the real vein pattern in the overlapping extraction. We propose this novel algorithm to detect the vein pattern from the original image.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.187-192
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• 2009

In this paper, we proposed an algorithm for personal identification of dorsal surface pattern of hand vein pattern using graph theory. Using dense ranee data images of the hand vein pattern, we used matching algorithm within the frame work of graph theory for the determination of the desired correspondence. Through preprocessing, the captured images are more sharp, clear and thinning. After thinning, the images are normalized and make graph with node and edge set. This normalized graph can make adjacent matrix. Each adjacent matrix from individual vein pattern are different. From examining the performance of individual vein patterns, we can approach performances well kind biometric technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.941-944
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• 2009

In this paper, we present a improved algorithm for thinning vein pattern. The vein image scanned using near infra-red is sliced in the horizontality or verticality direction, and then average value is gained from each slice image. Using curvature value changed from average value, search candidate part and extract vein pattern through re-searched candidate part in overlapping area. For the extracted vein pattern connecting, we proposed a DAL method that verify distance, angle and luminosity on pattern before tracking pattern extracted. The proposed improved thinning method is helpful for accurate connecting of vein pattern more than method used distance material in candidate part.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.261-263
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• 2005

In this paper, we implement an identification system using the vein image of the hand. The vein pattern is obtained in the grey-scale 2D image through the infrared-red imaging from back of the hand. Since the frame has lack of clearance, we use some enhancing methods such as the complement, addition, and multiplication to the image to increase the contrast. After Wiener filtering for smoothness of the vein pattern, we transform the image into the binary image with mean function. The binarized image is session thinned and the cross-points in the vein tree are obtained by calculating the number of pixels connected because the image is shaped as a tree. We choose the point and find the nearest to the center if it has majority, where we find the two end points of the selected line. We can get the angle between the two lines joined at the cross-point and store its coordinates, angle, and label the values. The values are used as the feature vector of the vein pattern. This procedure is similar to the human cognition sequences. It is shown that the proposed method is simple for the vein recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1190-1196
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• 2007

In this paper, we propose the biometrics system using hand vein pattern. This system is for management about person's entrance/exit in vessel USN. we select the biometrics method using hand vein pattern as adoptable method to vessel USN environment. Our experimental results show that preprocessing using two dimensional gabor filter achieves performance improvements over high pass filtering. Also, we compared our method with measured FAR(False Acceptance Rate) and FRR(False Rejection Rate) using pattern matching, the results show low error rate over high pass filtering. As a result, we verify the adoptability of biometrics system using hand vein pattern in management of person's entrance/exit in vessel.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.560-563
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• 1999

In this paper, we present an optimal hardware implementation for preprocessing of a person identification algorithm utilizing vein pattern of dorsal surface of hand. For the vein pattern recognition, the computational burden of the algorithm lies mainly in the preprocessing of the input images, especially in lowpass filtering. we could reduce the identification time to one tenth by hardware design of the lowpass filter compared to sequential computations. In terms of the computation accuracy, the simulation results show that the CSD code provided an optimized coefficient value with about 91.62% accuracy in comparison with the floating point implementation of current coefficient value of the lowpass filter. The post-simulation of a VHDL model has been performed by using the ModelSim$^{TM}$. The implemented chip operates at 20MHz and has the operational speed of 55.107㎳.㎳.