Latent-to-full palmprint comparison based on radial triangulation under forensic conditions

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. R. Wang, D. Ramos, J. Fiérrez, "Latent-to-full palmprint comparison based on radial triangulation under forensic conditions" in International Joint Conference on Biometrics (IJCB), Washington, D.C. (USA), 2011, 1 - 6.In forensic applications the evidential value of palmprints is obvious according to surveys of law enforcement agencies which indicate that 30 percent of the latents recovered from crime scenes are from palms. Consequently, developing forensic automatic palmprint identification technology is an urgent and challenging task which deals with latent (i.e., partial) and full palmprints captured or recovered at 500 ppi at least (the current standard in forensic applications) for minutiae-based offline recognition. Moreover, a rigorous quantification of the evidential value of biometrics, such as fingerprints and palmprints, is essential in modern forensic science. Recently, radial triangulation has been proposed as a step towards this objective in fingerprints, using minutiae manually extracted by experts. In this work we help in automatizing such comparison strategy, and generalize it to palmprints. Firstly, palmprint segmentation and enhancement are implemented for full prints feature extraction by a commercial biometric SDK in an automatic way, while features of latent prints are manually extracted by forensic experts. Then a latent-to-full palmprint comparison algorithm based on radial triangulation is proposed, in which radial triangulation is utilized for minutiae modeling. Finally, 22 latent palmprints from real forensic cases and 8680 full palmprints from criminal investigation field are used for performance evaluation. Experimental results proof the usability and efficiency of the proposed system, i.e, rank-l identification rate of 62% is achieved despite the inherent difficulty of latent-to-full palmprint comparison.The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007- 2013) under grant agreement number 23880

A Review on Palm Print Recognition System

Biometrics based authentication and recognition system helps to identify individuals based on various behavior and physical characteristics, which can be used for their unique personal identifications. Various physical characteristics like iris patterns, facial features, fingerprint patterns, retina patterns, palmprint patterns etc. are utilized for such identification purposes, Palm print recognition is counted as most suitable and reliable biometric recognition system because of its merits, such as user friendliness, low cost, high accuracy and high speed. A system that uses palmprint as recognize individuals involves the matching of the various principal lines, creases and wrinkles on the palm surface. Since the random orientations of muscles and tissues of the hand create the palmprint patterns during birth, these patterns are unique so no two palmprint patterns are exactly same for any individuals. This paper provides a detailed overview of palmprint recognition approaches, by describing the various steps and processing involve in palmprint identification

Multispectral Palmprint Encoding and Recognition

Palmprints are emerging as a new entity in multi-modal biometrics for human identification and verification. Multispectral palmprint images captured in the visible and infrared spectrum not only contain the wrinkles and ridge structure of a palm, but also the underlying pattern of veins; making them a highly discriminating biometric identifier. In this paper, we propose a feature encoding scheme for robust and highly accurate representation and matching of multispectral palmprints. To facilitate compact storage of the feature, we design a binary hash table structure that allows for efficient matching in large databases. Comprehensive experiments for both identification and verification scenarios are performed on two public datasets -- one captured with a contact-based sensor (PolyU dataset), and the other with a contact-free sensor (CASIA dataset). Recognition results in various experimental setups show that the proposed method consistently outperforms existing state-of-the-art methods. Error rates achieved by our method (0.003% on PolyU and 0.2% on CASIA) are the lowest reported in literature on both dataset and clearly indicate the viability of palmprint as a reliable and promising biometric. All source codes are publicly available.Comment: Preliminary version of this manuscript was published in ICCV 2011. Z. Khan A. Mian and Y. Hu, "Contour Code: Robust and Efficient Multispectral Palmprint Encoding for Human Recognition", International Conference on Computer Vision, 2011. MATLAB Code available: https://sites.google.com/site/zohaibnet/Home/code

Online palmprint identification

Author name used in this publication: Wai-Kin Kong2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Multimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review

This article is an overview of a current multimodal biometrics research based on fingerprint and palm-print. It explains the pervious study for each modal separately and its fusion technique with another biometric modal. The basic biometric system consists of four stages: firstly, the sensor which is used for enrolmen

Quadratic Projection Based Feature Extraction with Its Application to Biometric Recognition

This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes. We formulate quadratic matrix learning (QML) as a standard semidefinite programming (SDP) problem. However, the con- ventional interior-point SDP solvers do not scale well to the problem of QML for high-dimensional data. To solve the scalability of QML, we develop an efficient algorithm, termed DualQML, based on the Lagrange duality theory, to extract nonlinear features. To evaluate the feasibility and effectiveness of the proposed framework, we conduct extensive experiments on biometric recognition. Experimental results on three representative biometric recogni- tion tasks, including face, palmprint, and ear recognition, demonstrate the superiority of the DualQML-based feature extraction algorithm compared to the current state-of-the-art algorithm

Palmprint recognition using valley features

Author name used in this publication: David ZhangBiometrics Research Centre, Department of ComputingVersion of RecordPublishe

Data anonymization using pseudonym system to preserve data privacy

Data collection and storage in a large size is done on a routine basis in any company or organization. To this end, wireless network infrastructure and cloud computing are two widely-used tools. With the use of such services, less time is needed to attain the required output, and also managing the jobs will be simpler for users. General services employ a unique identifier for the aim of storing data in a digital database. However, it may be associated with some limitations and challenges. There is a link between the unique identifier and the data holder, e.g., name, address, Identity card number, etc. Attackers can manipulate a unique identifier for stealing the whole data. To get the data needed, attackers may even eavesdrop or guess. It results in lack of data privacy protection. As a result, it is necessary to take into consideration the data privacy issues in any data digital data storage. With the use of current services, there is a high possibility of exposure and leak of data/information to an unauthorized party during their transfer process. In addition, attacks may take place against services; for instance spoofing attacks, forgery attacks, etc. in the course of information transaction. To address such risks, this paper suggests the use of a biometric authentication method by means of a palm vein during the authentication process. Furthermore, a pseudonym creation technique is adopted to make the database record anonymous, which can make sure the data is properly protected. This way, any unauthorized party cannot gain access to data/information. The proposed system can resolve the information leaked, the user true identity is never revealed to others

Palmprint Recognition using Principle Component Analysis Implemented on TMS320C6713 DSP Processor

This paper presents a human identification system using eigen-palm images. The proposed method consists of three main stages. The preprocessing stage computes the palmprint images to capture important information and produce a better representation of palmprint image data. The second stage extracts significant features from palmprint images and reduces the dimension of the palmprint image data by applying the principal component analysis (PCA) technique. Low-dimensional features in the feature space are assumed to be Gaussian. Thus, the Euclidean distance classifier can be used in the matching process to compare test image with the template. The proposed method is tested using a benchmark PolyU dataset. Experimental results show that the best achieved recognition rate is 97.5% when the palmprint image is represented using 34 PCA coefficients. Moreover, the Euclidean distance classifier is implemented on a digital signal processor (DSP) board. Implementing the proposed algorithm using the DSP processor achieves better performance in computation time compared with a personal computer-based syste