A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae) and fingerprint macro features (singularity points) for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys), are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance

Usability analysis of a novel biometric authentication approach for android-based mobile devices

Mobile devices are widely replacing the standard personal computers thanks to their small size and user-friendly use. As a consequence, the amount of information, often confidential, exchanged through these devices is raising. This makes them potential targets of malicious network hackers. The use of simple passwords or PIN are not sufficient to provide a suitable security level for those applications requiring high protection levels on data and services. In this paper a biometric authentication system, as a running Android application, has been developed and implemented on a real mobile device. A system test on real users has been also carried out in order to evaluate the human-machine interaction quality, the recognition accuracy of the proposed technique, and the scheduling latency of the operating system and its degree of acceptance. Several measures, such as system usability, users satisfaction, and tolerable speed for identification, have been carried out in order to evaluate the performance of the proposed approach

An Advanced Technique for User Identification Using Partial Fingerprint

User identification is a very interesting and complex task. Invasive biometrics is based on traits uniqueness and immutability over time. In forensic field, fingerprints have always been considered an essential element for personal recognition. The traditional issue is focused on full fingerprint images matching. In this paper an advanced technique for personal recognition based on partial fingerprint is proposed. This system is based on fingerprint local analysis and micro-features, endpoints and bifurcations, extraction. The proposed approach starts from minutiae extraction from a partial fingerprint image and ends with the final matching score between fingerprint pairs. The computation of likelihood ratios in fingerprint identification is computed by trying every possible overlapping of the partial image with complete image. The first experimental results conducted on the PolyU (Hong Kong Polytechnic University) free database show an encouraging performance in terms of identification accuracy

A new algorithm for minutiae extraction and matching in fingerprint

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A novel algorithm for fingerprint template formation and matching in automatic fingerprint recognition has been developed. At present, fingerprint is being considered as the dominant biometric trait among all other biometrics due to its wide range of applications in security and access control. Most of the commercially established systems use singularity point (SP) or ‘core’ point for fingerprint indexing and template formation. The efficiency of these systems heavily relies on the detection of the core and the quality of the image itself. The number of multiple SPs or absence of ‘core’ on the image can cause some anomalies in the formation of the template and may result in high False Acceptance Rate (FAR) or False Rejection Rate (FRR). Also the loss of actual minutiae or appearance of new or spurious minutiae in the scanned image can contribute to the error in the matching process. A more sophisticated algorithm is therefore necessary in the formation and matching of templates in order to achieve low FAR and FRR and to make the identification more accurate. The novel algorithm presented here does not rely on any ‘core’ or SP thus makes the structure invariant with respect to global rotation and translation. Moreover, it does not need orientation of the minutiae points on which most of the established algorithm are based. The matching methodology is based on the local features of each minutiae point such as distances to its nearest neighbours and their internal angle. Using a publicly available fingerprint database, the algorithm has been evaluated and compared with other benchmark algorithms. It has been found that the algorithm has performed better compared to others and has been able to achieve an error equal rate of 3.5%

Portable and Efficient Fingerprint Authentication System Based on a Microcontroller

This paper presents the design of a fingerprint authentication system based on a simple microcontroller and the fingerprint sensor. The circuit diagram and details regarding the procedure are included. The system was programed in MPLAB and then embedded into the microcontroller. Communication between the PIC and sensor is by RS232 protocol. The results show that the system recognizes the fingerprint in less than 1 second. It is portable and there is no need for image processing. Furthermore, the system shows a high effectiveness when storing and verifying fingerprints

Embedded Biometric Sensor Devices: Design and Implementation on Field Programmable Gate Array

During the research activity in my Ph.D. course, I thoroughly studied the biometric systems and the relevant design and implementation techniques allowing the employment of such systems in embedded devices. I focused my attention on the fingerprint-based recognition and classification systems, and on their implementation on Field Programmable Gate Array (FPGA) devices. I was prompted to study biometric systems mainly because these systems may play a key role in the new emerging market of mobile devices (for example, they are recently available in the new generation of Apple and Samsung smart phones). Such market is rapidly growing and influencing the way people use network resources and functionalities (such as commercial, banking, and government services), requiring a security level higher than in the past. Consequently, novel design techniques and technologies for user recognition and are required to be investigated, in order to provide a secure services and resources access. The traditional authentication systems based on username and password are not able to guarantee a suitable protection level. Unlike password, instead, user biometric information is unique and unchangeable; therefore the biometric identity has the advantage to guarantee that only the authorized users have access to available resources and services. However, traditional biometric approaches involves interactions among a large number of entities: passive access points for user biometric trait acquisition, networked databases for user biometric identity storing, and trusted servers running the user recognition systems. So, traditional systems usually undergo several types of attacks, such as Communication Attack (attacking the channel between the server and the database), Replay Attack (replication of user biometric trait processed during the acquisition phase), and Database Attack (manipulation of the stored user biometric identity). Embedded architectures, instead, provide a more secure and flexible infrastructure, since all elaboration steps are performed on board, so biometric identities are securely managed and stored inside the system without any data leaking out. The goal of this thesis is to illustrate the analysis and results of my research activity focused on the design and development of new fingerprint-based recognition systems for embedded devices. The study of the state-of-the-art about biometric systems led me to realize novel approaches to improve the performance of standard systems in order to enable their employment in embedded devices architectures. Most common literature approaches used to implement fingerprint-based recognition and classification systems are reported to provide a starting-point for understanding the contribution of this work. There are many literature approaches to deal with software systems, but few on design and implementation of embedded hardware prototypes. Referring to the developed and proposed fingerprint-based systems, this thesis represents an advancement of embedded biometrics respect to state-of-the-art. The step-over proposed in this work is focused on: 1. a heuristic fingerprint classification technique, requiring only a little set of images as training dataset; 2. an advanced matching technique for personal recognition based on partial fingerprint, able to enhance the system accuracy; 3. the design and implementation of an efficient fingerprint features extractor; 4. the design and implementation of a quality evaluator of raw fingerprint images (able to identify poor quality areas, such as dry and moist portions), allowing to define a novel flow of image processing steps for user recognition. This thesis is divided into two parts, creating a path connecting the state-of-the-art about biometric systems and the novel implemented approaches. The knowledge of the state-of-the-art about biometrics is fundamental to understand the step over presented in this work. For this reason, in the first part, general characteristics of biometric systems are presented with particular reference to fingerprint-based approaches used in literature to realize embedded systems. The second part proposes the developed innovative sensor. A novel flow of image processing steps for user recognition is outlined. Successively, an efficient micro and macro fingerprint features extractor is illustrated. Then, an advanced matching technique for personal recognition using partial fingerprints is presented. Finally, an innovative fingerprint classification approach based on the fusion of Fuzzy C-Means and Naive-Bayes technique is detailed. Experimental results and comparisons with analogous literature systems show the effectiveness on the proposed sensor. All the innovative approaches proposed in this thesis have been published in international conferences and journals

An Efficient Reconfigurable Architecture for Fingerprint Recognition

The fingerprint identification is an efficient biometric technique to authenticate human beings in real-time Big Data Analytics. In this paper, we propose an efficient Finite State Machine (FSM) based reconfigurable architecture for fingerprint recognition. The fingerprint image is resized, and Compound Linear Binary Pattern (CLBP) is applied on fingerprint, followed by histogram to obtain histogram CLBP features. Discrete Wavelet Transform (DWT) Level 2 features are obtained by the same methodology. The novel matching score of CLBP is computed using histogram CLBP features of test image and fingerprint images in the database. Similarly, the DWT matching score is computed using DWT features of test image and fingerprint images in the database. Further, the matching scores of CLBP and DWT are fused with arithmetic equation using improvement factor. The performance parameters such as TSR (Total Success Rate), FAR (False Acceptance Rate), and FRR (False Rejection Rate) are computed using fusion scores with correlation matching technique for FVC2004 DB3 Database. The proposed fusion based VLSI architecture is synthesized on Virtex xc5vlx30T-3 FPGA board using Finite State Machine resulting in optimized parameters