An Embedded Real-Time Biometric Recognition System for Defense system

Abstract

In this project, we propose a real-time embedded finger-vein recognition system for authentication on mobile devices. The system is implemented on an embedded platform and equipped with a novel finger-vein recognition algorithm. The proposed system consists of three hardware modules: image acquisition module, embedded main board, and human machine communication module. The structure diagram of the system is 1. The image acquisition module is used to collect finger-vein images. The Embedded main board including the Microcontroller chip, memory (flash), and communication port is used to execute the finger-vein recognition algorithm and communicate with the peripheral device. The human machine communication module (LED or keyboard) is used to display recognition results and receive inputs from users. Index Terms: finger-vein recognition; biometrics; mobile Devices; DSP I. Introduction Private information is traditionally provided by using Passwords or Personal Identification Numbers (PINs), which are easy to implement but is vulnerable to the risk of exposure and being forgotten. Biometrics, which uses human physiological or behavioral features for personal Identification, has attracted more and more attention and is becoming one of the most popular and promising alternatives to the traditional password or PIN based authentication techniques (1). Moreover, some multimedia content in consumer electronic appliances can be secured by biometrics (2). There is a long list of available biometric patterns, and many such systems have been developed and implemented, including those for the face, iris, fingerprint, palm print, hand shape, voice, signature, and gait. Notwithstanding this great and increasing variety of biometrics patterns, no biometric has yet been developed that is perfectly reliable or secure. For example, fingerprints and palm prints are usually frayed; voice, signatures, hand shapes and iris images are easily forged; face recognition can be made difficult by occlusions or face-lifts (3); and biometrics, such as fingerprints and iris and face recognition, are susceptible to spoofing attacks, that is, the biometric identifiers can be copied and used to create artifacts that can deceive many currently available biometric devices. The great challenge to biometrics is thus to improve recognition performance in terms of both accuracy and efficiency and be maximally resistant to deceptive practices. To this end, many researchers have sought to improve reliability and frustrate spoolers by developing biometrics that are highly individuating; yet at the same time, present a highly complex, hopefully insuperable challenge to those who wish to defeat them (4). Specially for consumer electronics applications, biometrics authentication systems need to be cost-efficient and easy to implement (5). The finger-vein is a promising biometric pattern for personal identification in terms of its security and convenience (6). Compared with other biometric traits, the finger-vein has the following advantages (7): (1) the vein is hidden inside the body and is mostly invisible to human eyes, so it is difficult to forge or steal. (2) The non-invasive and contactless capture of finger-veins ensures both convenience and hygiene for the user, and is thus more acceptable. (3) The finger-vein pattern can only be taken from a live body. Therefore, it is a natural and convincing proof that the subject whose finger-vein is successfully captured is alive. We designed a special device for acquiring high quality finger-vein images and propose a DSP based embedded platform to implement the finger-vein recognition system in the present study to achieve better recognition performance and reduce computational cost.The rest of this paper is organized as follows. An overview of the proposed system is given in Section 2. The device for finger-vein image acquisition is introduced in Section 3. Our recognition method is addressed in Section 4. Experimental results are then presented in Section 5. Finally, concluding remarks are given in Section 6.