259 research outputs found

    Palm Vein Recognition: A Review

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    A review: personal identification based on palm vein infrared pattern

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    Palm vein recognition is the latest biometrics technique used and researches currently. This method achieved high performance in identification due to the complexity of vein pattern on the palm. This studies proposed a review of overall process of vein recognition and vein recognition techniques. In particular, this studies is systematically described in three parts which is vein image acquisition and preprocessing, feature extraction and decision matching. According to the available work, various approaches for different kind of features extractions, palm vein segmentation and overall process will be discussed in this paper

    A Review: Personal Identification Based on Palm Vein Infrared Pattern

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    Palm vein recognition is the latest biometrics technique used and researches currently. This method achieved high performance in identification due to the complexity of vein pattern on the palm. This studies proposed a review of overall process of vein recognition and vein recognition techniques. In particular, this studies is systematically described in three parts which is vein image acquisition and preprocessing, feature extraction and decision matching. According to the available work, various approaches for different kind of features extractions, palm vein segmentation and overall process will be discussed in this paper

    A Filtering Method for SIFT based Palm Vein Recognition

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    A key issue with palm vein images is that slight movements of fingers and the thumb or changes in the hand pose can stretch the skin in different areas and alter the vein patterns. This can produce palm vein images with an infinite number of variations for a given subject. This paper presents a novel filtering method for SIFT-based feature matching referred to as the Mean and Median Distance (MMD) Filter, which checks the difference of keypoint coordinates and calculates the mean and the median in each direction in order to filter out the incorrect matches. Experiments conducted on the 850nm subset of the CASIA dataset show that the proposed MMD filter can maintain correct points and reduce false positives that were detected by other filtering methods. Comparison against existing SIFT-based palm vein recognition systems demonstrates that the proposed MMD filter produces excellent performance recording lower Equal Error Rate (EER) values

    Biometric Identification Systems: Feature Level Clustering of Large Biometric Data and DWT Based Hash Coded Bar Biometric System

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    Biometric authentication systems are fast replacing conventional identification schemes such as passwords and PIN numbers. This paper introduces a novel matching scheme that uses a image hash scheme. It uses Discrete Wavelet Transformation (DWT) of biometric images and randomized processing strategies for hashing. In this scheme the input image is decomposed into approximation, vertical, horizontal and diagonal coefficients using the discrete wavelet transform. The algorithm converts images into binary strings and is robust against compression, distortion and other transformations. As a case study the system is tested on ear database and is outperforming with an accuracy of 96.37% with considerably low FAR of 0.17%. The performance shows that the system can be deployed for high level security applications

    Advancing the technology of sclera recognition

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    PhD ThesisEmerging biometric traits have been suggested recently to overcome some challenges and issues related to utilising traditional human biometric traits such as the face, iris, and fingerprint. In particu- lar, iris recognition has achieved high accuracy rates under Near- InfraRed (NIR) spectrum and it is employed in many applications for security and identification purposes. However, as modern imaging devices operate in the visible spectrum capturing colour images, iris recognition has faced challenges when applied to coloured images especially with eye images which have a dark pigmentation. Other issues with iris recognition under NIR spectrum are the constraints on the capturing process resulting in failure-to-enrol, and degradation in system accuracy and performance. As a result, the research commu- nity investigated using other traits to support the iris biometric in the visible spectrum such as the sclera. The sclera which is commonly known as the white part of the eye includes a complex network of blood vessels and veins surrounding the eye. The vascular pattern within the sclera has different formations and layers providing powerful features for human identification. In addition, these blood vessels can be acquired in the visible spectrum and thus can be applied using ubiquitous camera-based devices. As a consequence, recent research has focused on developing sclera recog- nition. However, sclera recognition as any biometric system has issues and challenges which need to be addressed. These issues are mainly related to sclera segmentation, blood vessel enhancement, feature ex- traction, template registration, matching and decision methods. In addition, employing the sclera biometric in the wild where relaxed imaging constraints are utilised has introduced more challenges such as illumination variation, specular reflections, non-cooperative user capturing, sclera blocked region due to glasses and eyelashes, variation in capturing distance, multiple gaze directions, and eye rotation. The aim of this thesis is to address such sclera biometric challenges and highlight the potential of this trait. This also might inspire further research on tackling sclera recognition system issues. To overcome the vii above-mentioned issues and challenges, three major contributions are made which can be summarised as 1) designing an efficient sclera recognition system under constrained imaging conditions which in- clude new sclera segmentation, blood vessel enhancement, vascular binary network mapping and feature extraction, and template registra- tion techniques; 2) introducing a novel sclera recognition system under relaxed imaging constraints which exploits novel sclera segmentation, sclera template rotation alignment and distance scaling methods, and complex sclera features; 3) presenting solutions to tackle issues related to applying sclera recognition in a real-time application such as eye localisation, eye corner and gaze detection, together with a novel image quality metric. The evaluation of the proposed contributions is achieved using five databases having different properties representing various challenges and issues. These databases are the UBIRIS.v1, UBIRIS.v2, UTIRIS, MICHE, and an in-house database. The results in terms of segmen- tation accuracy, Equal Error Rate (EER), and processing time show significant improvement in the proposed systems compared to state- of-the-art methods.Ministry of Higher Education and Scientific Research in Iraq and the Iraqi Cultural Attach´e in Londo

    Biometric recognition based on the texture along palmprint lines

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    Tese de Mestrado Integrado. Bioengenharia. Faculdade de Engenharia. Universidade do Porto. 201

    Robust iris recognition under unconstrained settings

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    Tese de mestrado integrado. Bioengenharia. Faculdade de Engenharia. Universidade do Porto. 201

    Handbook of Vascular Biometrics

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    Handbook of Vascular Biometrics

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    This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers
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