Palm Vein Recognition Using Directional Features Derived from Local Binary Patterns

Wenjing Lu,Meini Li,Lei Zhang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5

Vein-based biometrics is a newly developed technology for personal recognition, and it is widely used in practice and intensively studied. This paper proposes a method for palm vein recognition based on the directional information derived from local binary patters. In the proposed method, palm vein images are firstly enhanced using a multi-scale Gaussian matched filter to emphasize vein patterns before feature extraction. After that, local binary patterns are extracted from the enhanced palm vein images. Considering that the direction is the most discriminative feature of veins, the directional information is then computed from the local binary patterns. The computed palm vein features are represented as binary series, therefore, similarities can be computed efficiently by binary operation. Experiments carried out over the near infer-red band of the PolyU multispectral database shows the superiority of the proposed method on verification accuracy to some state-of-the-art literatures.

A Palm Vein Recognition System based on a Support Vector Machine

Vijayakumar Ponnusamy,Abhijit Sridhar,Arun Baalaaji,M. Sangeetha 대한전자공학회 2019 IEIE Transactions on Smart Processing & Computing Vol.8 No.1

Palm vein authentication is among the recent research in the field of access control applications. Because palm veins are tough to forge, they act as a reliable metric in security applications. Accurate extraction of palm veins is challenging in the presence of various dynamics, such as variant light conditions, variations in palm vein patterns from person to person, the cleanliness of the hand, etc. This paper presents a robust recognition process that makes use of a ridge filter for vein pattern extraction, and local binary patterns (LBP) for feature extraction. The ridge filter takes the major eigenvalue of the Hessian matrix, which contains the second-order derivative of the image pixels. The eigenvalue is then processed using LBP feature extraction from the vein patterns. Finally, a support vector machine is used for classification of subsequent images. The result shows that the system can provide accuracy of 89%, with a computation time of 0.423s. The false acceptance rate and false rejection rate were also evaluated as benchmark parameters, which show significantly good performance.

Development of Data Fusion Human Identification System Based on Finger-Vein Pattern-Matching Method and photoplethysmography Identification

Kuk Won Ko,Jiyeon Lee,Hongsuk Moon,Sangjoon Lee 한국인터넷방송통신학회 2015 International Journal of Internet, Broadcasting an Vol.7 No.2

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.

지정맥 인식을 위한 특징 검출 알고리즘 개발

김태훈 ( Taehoon Kim ),이상준 ( Sangjoon Lee ) 한국정보처리학회 2018 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.7 No.9

본 연구는 지정맥 인식에 중요한 정맥 패턴 특징검출을 위한 알고리즘이다. 특징검출 알고리즘은 패턴인식 시 인식결과에 많은 영향을 끼치므로 중요하다. 인식률은 손가락 위치 변화에 따라 기준도 변화되므로 저하되는 특징을 가지고 있다. 또한, 손가락에 적외선 광을 조사하여 획득한 영상은 영상 배경과 혈관 패턴을 분리하기에 어렵고, 영상 전처리과정을 수행하므로 검출시간이 증대되는 특징을 가지고 있다. 이를 위해, 제시하는 알고리즘은 영상 전처리과정이 없이 수행되어 검출 시간을 줄일 수 있고, 지정맥 영상에 SWDA(Shifted Waveform Data Analysis) 알고리즘을 적용하여 손가락 마디 위치 및 정맥 패턴 검출이 가능한 특징을 가지고 있다. 적외선 투과율이 낮아 상대적으로 어두운 정맥 영상도 검출 오류 최소화가 가능한 특징을 보였다. 또한, 손가락 마디 위치는 분류 단계에서 기준으로 활용하면 인식률 저하를 보완할 수 있는 특징을 가지고 있다. 추후 손바닥, 손목 등 신체 여러 인식분야에 제안하는 알고리즘을 적용한다면 생체 특징 검출 정확도 향상 및 인식 수행 시간 감소에 기여할 것으로 기대된다. 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.

Development of Data Fusion Human Identification System Based on Finger-Vein Pattern-Matching Method and photoplethysmography Identification

Ko, Kuk Won,Lee, Jiyeon,Moon, Hongsuk,Lee, Sangjoon The Institute of Internet 2015 International Journal of Internet, Broadcasting an Vol.7 No.2

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.

Development of Human Identification System Based on Simple Finger-Vein Pattern-Matching Method for Embedded Environments

Kuk Won Ko,Jiyeon Lee,Mehrdad Ahmadi,Sangjoon Lee 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.5

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, and finger-vein have become increasingly important in the personal security field, including door access control, finance security, and electronic passport. Finger-vein images can be captured under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. Difficulties in recognizing finger-vein images include the use of a complex algorithm for noise reduction, image re-construction, and rotation invariance in the pattern-matching algorithm. In this paper, we use a compact CMOS camera with a penetrating infrared LED light source. 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.

A Distance Metric Computation Model for the Design and Development of Palm Vein Recognition System

Shriram D. Raut,Dr. Vikas T. Humbe 보안공학연구지원센터 2015 International Journal of Bio-Science and Bio-Techn Vol.7 No.6

Palm vein recognition is a part of physiological biometric uses blood vessel structure for the identification. The blood transfusion from body parts to heart is made by the blood vein. The blood vein carries de-oxygenated hemoglobin that can be sensed under near infrared light. The pattern classification proposes a design cycle to build a system for recognition. The image database was obtained from Hong Kong Polytechnic University. The experimentation was carried on palm vein image captured under near infrared light. The distance metric computation was done and stored in the form of the template. The paper discuss about the experimentation of Euclidean distance metric on the palm vein feature extracted binary image using Gabor filter and canny edge detection.

Zr-Ti-Cu-Ni-Be 합금으로 제조된 상용 골프클럽헤드의 부위별 물리적 특성 및 기계적 거동

최영철,홍순익,Choi, Young-Chul,Hong, Sun-Ig 한국재료학회 2005 한국재료학회지 Vol.15 No.11

The deformation behavior of a bulk amorphous and crystallized amorphous $Zr_{22.5}Ti_{14}Cu_{12.5}Ni_{10}Be_{22.5}$ alloy extracted from a commercial golf club head was characterized at room temperature ana $300^{\circ}C$. At room temperature, amorphous specimens revealed higher yield stress and ductility than partially crystallized alloy specimens. Amorphous alloy displayed some plasticity before fracture, which resulted from strain hardening and repeated crack initiation and propagation. The fracture is mainly localized on one major shear band, and the compressive fracture angle of the amorphous specimen between the stress axis and the fracture plane was about $40^{\circ}$ Scanning electron microscope observations revealed mainly a vein-like structure in the amorphous alloy But the fracture surface of partially crystallized amorphous alloy consisted of vein-like and featureless fracture structure. The partially crystallized alloy extracted from the thick part of the club fractured in the elastic region, at a much lower stress level than the amorphous, suggesting that relatively coarse crystal particles formed during cooling cause the brittle fracture.

손가락 정맥 영상의 차 영상 기반 가시성 향상 방법

김태형,이의철 인문사회과학기술융합학회 2018 예술인문사회융합멀티미디어논문지 Vol.8 No.6

최근 첨단 기술 발전에 따른 정보의 가치가 높아져가고 그에 따라 정보 보호에 대한 중요성도 강조된다. 정보 보호 방법에는 패스워드, PIN, 생체정보 등이 포함되어있다. 생체 정보 중에선 행동학적 특성을 사용하는 방법, 생물학적 특성을 사용하는 방법으로 나뉜다. 우리는 여러 방법 중에서 생물학적 특성에 관심을 가지고 정맥 인식에 대해 연구를 진행했다. 정맥 인식은 사람마다 다른 손바닥, 손등, 손가락 등의 혈관 패턴을 이용해 신원을 확인하는 인식 기법이다. 이 기법은 시간이 지나면서 변하지 않는 신체의 내부 특성을 사용한다는 점과 위생적으로 안전하고 보안성 측면에서도 우수한 능력을 보이고 있다. 그러나 피부 층에서 광 산란으로 인해 이미지에서 정맥의 패턴이 잘 보이지 않는 문제와 이미지가 광학적으로 흐려지는 문제가 있다. 본 논문에서는 영상에서 정맥 패턴의 가시성을 향상시키기 위해 영상의 이동차이 처리 방법을 제안한다. 이 방법에선 영상 이동, 영상 차이 처리, 영상 차이 합병, 히스토그램 평활화 순서를 거쳐 영상의 가시성을 향상 시켰다. Recently, according to increment of the value of information due to the development of advanced technology, the importance of information security has also been emphasized. Methods for protecting information include passwords, PINs, and biometric information. Biometrics can be divided into two categories such as behavioral and physiological methods. Our proposed method is focused on vein recognition method which is the one of physiological biometrics. Vein recognition is a recognition technique that uses different vein patterns such as palms, hands, and fingers to identify people. This show the ability to use the internal characteristics of the body that does not change over time, and is also hygienically safe and excellent in security. However, in the skin layer, there is a problem that the vein pattern is not visible in the image due to the light scattering and the image is optically blurred. In this paper, we propose a movement difference processing method for improving the visibility of vein patterns in images. In this method, we improved the visibility of the image through pixel shift, pixel substraction, and pixel merge. As a result, it was confirmed that the vein pattern was visually more visible.

Finger Vein Recognition Using Generalized Local Line Binary Pattern

( Yu Lu ),( Sook Yoon ),( Shan Juan Xie ),( Jucheng Yang ),( Zhihui Wang ),( Dong Sun Park ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5

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).