Local Descriptor Approach to Wrist Vein Recognition with DVH-LBP Domain Feature Selection Scheme

Local Binary Pattern (LBP) is one of the well-known image recognition descriptors for texture-based images due to its superiority. LBP can represent texture well due to its ability to discriminate and compute efficiency. However, when it is used to describe textures that are barely visible, such as vein images (especially contactless vein), its discrimination ability is reduced, which leads to lower performance. LBP has extensively been implemented for features extraction in recognition system of hand, eye, face, eye, and other images. Nowadays, there are a lot of developments of hand recognition systems as a hand is a part of the body that can be easily used in the recognition process and it is easier to contact the sensor when taking the image (user-friendly). In particular, a hand consists of various parts that can be used, such as palm and fingers. Other parts like dorsal and wrist can also be used as they have unique characteristics, i.e., they are different from each other, and they do not change with ages. Changes in pixel intensity can be derived from skeletal vein images to distinguish individuals in palm vein recognition. In the previous paper, we proposed a method diagonal, vertical, horizontal local binary pattern (DVH-LBP) for implementing the palm vein recognition system successfully. Through this work, we improve our previous procedure and implement the improved method for recognizing wrist. In particular, this study proposes a new and robust directional extraction technique for encoding the functions of the wrist vein in a simple representation of binary numbers. Simulation results show the low equal error rate (ERR) of the proposed technique is 0.012, and the recognition rate is 99.4%

Miniaturización y automatización de sistema de captura de imágenes vasculares

La identificación biométrica es la identificación basada en las características biológicas, físicas o de comportamiento de una persona. Desde hace ya varios años es uno de los métodos más usados para confirmar la identidad de una persona. Su excelente tasa de reconocimiento, sumado a su riesgo prácticamente nulo de falsificación (si el sensor dispone de mecanismos de detección de sujeto vivo), ha hecho notable su uso para infinidad de aplicaciones. Por otra parte hay modalidades o mecanismos de identificación biométrica más desarrollados que otros, debido a su mayor antigüedad. En el presente Trabajo de Fin de Grado se va a desarrollar una parte de un sistema de identificación vascular. Partiendo del sensor de captura de imágenes vasculares ya construido, nos vamos a encargar de que la máquina tome las imágenes más apropiadas (la que mejor nos vengan para el sistema de identificación biométrica) y que lo haga de manera automática. Si a este trabajo se le añadiera una base de datos (que almacenara las imágenes de los sujetos) y un algoritmo capaz de comparar el patrón de las venas de la mano, se podría obtener un sistema de identificación biométrico completo y valido para gran variedad de usos, como el paso a zonas privadas, el reconocimiento para algún tipo de transacción, etc.Biometric identification is the identification based on biological, physical or behavioral characteristics of a person. For several years is one of the most used methods to confirm the identity of a person. Its excellent recognition rate, coupled with low risk of forgery, has made remarkable its use for many applications. On the other hand there are methods or biometric identification mechanisms more developed than others, due to their greater antiquity. This Final Project Grade is going to develop a portion of a vein identification system. Starting from the machine and vascular imaging built, we`re going to take care of the machine to pick the most appropriate images (the best one that applies to the biometric identification system). If this work is augmented by a database (which will store the images of subjects) and an algorithm able to compare the pattern of the veins of the hand, you will get a full biometric identification system and valid for a huge variety of uses such as granting access to private areas, recognition for some sort of transaction, etc.Ingeniería Electrónica Industrial y Automátic

Exploration of Low SWaP(Size,Weight and Power) Diffuse Optical Tomography and Imaging Technique for Biometrics

Title from PDF of title page, viewed September 19, 2023Thesis advisor: Rahman MostafizurVitaIncludes bibliographical references (pages 51-55)Thesis (M.S.)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 2023There have been significant advancements in biometric systems, with a particular focus on Iris, facial, and fingerprint recognition. My research, however, is centered around wrist vein recognition and involves the development of two biometric modalities: wrist vein imaging and Diffuse Optical Tomography (DoT) data. The primary objective is to create a hardware system with low size, weight, and power consumption. The proposed setup utilizes IR Light as the light source. The IR light penetrates and scatters through the layers of tissue, and when it encounters the Blood volume, deoxygenated blood absorbs the IR light, causing the vein to appear darker. Meanwhile, the DoT data captures the biological characteristics using a photodiode on the wrist when exposed to IR light. These two methods serve as low-cost biometric alternatives. The ultimate goal is to develop a wearable hardware system capable of real-time data capturing with high accuracy. Additionally, it should be robust to environmental changes and operate on ultra-low power consumption.Hardware design -- Test methodology -- Results and discussion -- Conclusion and future wor

Biometric Person Identification Using Near-infrared Hand-dorsa Vein Images

Biometric recognition is becoming more and more important with the increasing demand for security, and more usable with the improvement of computer vision as well as pattern recognition technologies. Hand vein patterns have been recognised as a good biometric measure for personal identification due to many excellent characteristics, such as uniqueness and stability, as well as difficulty to copy or forge. This thesis covers all the research and development aspects of a biometric person identification system based on near-infrared hand-dorsa vein images. Firstly, the design and realisation of an optimised vein image capture device is presented. In order to maximise the quality of the captured images with relatively low cost, the infrared illumination and imaging theory are discussed. Then a database containing 2040 images from 102 individuals, which were captured by this device, is introduced. Secondly, image analysis and the customised image pre-processing methods are discussed. The consistency of the database images is evaluated using mean squared error (MSE) and peak signal-to-noise ratio (PSNR). Geometrical pre-processing, including shearing correction and region of interest (ROI) extraction, is introduced to improve image consistency. Image noise is evaluated using total variance (TV) values. Grey-level pre-processing, including grey-level normalisation, filtering and adaptive histogram equalisation are applied to enhance vein patterns. Thirdly, a gradient-based image segmentation algorithm is compared with popular algorithms in references like Niblack and Threshold Image algorithm to demonstrate its effectiveness in vein pattern extraction. Post-processing methods including morphological filtering and thinning are also presented. Fourthly, feature extraction and recognition methods are investigated, with several new approaches based on keypoints and local binary patterns (LBP) proposed. Through comprehensive comparison with other approaches based on structure and texture features as well as performance evaluation using the database created with 2040 images, the proposed approach based on multi-scale partition LBP is shown to provide the best recognition performance with an identification rate of nearly 99%. Finally, the whole hand-dorsa vein identification system is presented with a user interface for administration of user information and for person identification

Mecanismos de captura y procesado de imágenes de venas para identificación personal

Actualmente la identificación biométrica para el acceso a recintos o servicios está cobrando bastante importancia. La biometría es una tecnología que, además de realizar funciones de reconocimiento, aporta mayores niveles de seguridad que otros métodos de identificación externos, al llevar intrínsecamente la información en el cuerpo. La identificación biométrica vascular ofrece un futuro muy prometedor en ambos aspectos. La mayoría de los sistemas biométricos se basan en sistemas hardware (HW) para la captura de muestras del usuario más una solución software (SW) para el procesado de las mismas. La tarea de la investigación en biometría vascular hoy en día es crear sistemas fiables y seguros para obtener soluciones aplicables. En esta Tesis, hemos propuesto dos importantes contribuciones a la identificación mediante esta modalidad biométrica: 1. Un sistema hardware novedoso y económico para la captura de patrones y muestras del usuario, tanto de palma como de muñeca, que ofrece imágenes de una calidad suficiente para su procesado posterior. Además, a diferencia de los trabajos previos realizados, las especificaciones y diseño de este sistema se ofrecen abiertamente a la comunidad científica. 2. Un sistema de procesamiento de las imágenes de las venas extraídas, basado en las conocidas función Gaussiana y función de Convolución, y un nuevo sistema de toma de decisiones, basado en una comparación orientable de las líneas extraídas apoyado con el dato obtenido del ancho de la muñeca de cada usuario. Esto también se ofrece a la comunidad científica, mostrando todas las fases del proceso, al contrario de lo que ocurre con las escasas publicaciones existentes que se analizarán a lo largo del presente documento. Para demostrar la viabilidad de esta propuesta se ha desarrollado e implementado un sistema HW y SW completo, y se ha probado finalmente con 100 usuarios de diferentes edades, razas y sexo, obteniendo los resultados mostrados al final de esta Tesis que confirman la viabilidad futura de la solución propuesta. Finalmente se indican las líneas de investigación futuras para mejorar la solución y obtener mejores resultados, así como para obtener una mayor comodidad a la hora de la captura de muestras del usuario. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Biometric identification for the compartment or service access is more and more important nowadays. Biometrics is a technology which brings higher security leves than other external identification methods because the information is inherently inside the human body, apart from providing recognition functions. Vascular biometric identification offers a very hopeful future in both subjects. Most of the biometric systems are based on hardware systems (HW) in order to take user samples in addition to software systems (SW) so as to process these ones. The investigation task in vascular biometrics is focused on creating reliable and secure systems at this moment to obtain relevant solutions. We propose in this PhD thesis two important contributions for the identification using the above mentioned biometric modality: 1. A novel and economic hardware system in order to capture user patterns and samples, palm and wrist both, which offers images with enough quality for its further processing. Furthermore, unlike the previous found works, the design and specifications of this system are available openly to the scientific community. 2. An image processing system for the extracted veins images, based on the well-known Gauss and Convolution functions, and a novel decision making system, based on an orientation comparison of the extracted lines with the support of the wrist width value obtained for every user. All of this is also available to the scientific community, explaining every step in the whole process, unlike what happens with the limited existing scientific publications, which will be discussed along the present document. A complete HW and SW system has been designed and developed so as to demonstrate the viability of these works, and this one has been finally tested with 100 users from different ages, races and sex, obtaining the results shown at the end of this PhD thesis, which confirm the future viability of the proposed solution. Finally, future investigation points are given to enhance the solution and to get better results, as well as to obtain a major comfort for the user sample captures