Architectures for efficient face authentication in embedded systems

Abstract

Biometrics represent a promising approach for reliable and secure user authentication. However, they have not yet been widely adopted in embedded systems, particularly in resource-constrained devices such as cell phones and personal digital assistants (PDAs). In this paper, we investigate the challenges involved in using face-based biometrics for authenticating a user to an embedded system. To enable high authentication accuracy, we consider robust face verifiers based on principal component analysis/linear discriminant analysis (PCA-LDA) algorithms and Bayesian classifiers, and their combined use (multi-modal biometrics). Since embedded systems are severely constrained in their processing capabilities, algorithms that provide sufficient accuracy tend to be computationally expensive, leading to unacceptable authentication times. On the other hand, achieving acceptable performance often comes at the cost of degradation in the quality of results.Our work aims at developing embedded processing architectures that improve face verification speed with minimal hardware requirements, and without any compromise in verification accuracy. We analyze the computational characteristics of face verifiers when running on an embedded processor, and systematically identify opportunities for accelerating their execution. We then present a range of targeted hardware and software enhancements that include the use of fixed-point arithmetic, various code optimizations, application-specific custom instructions and co-processors, and parallel processing capabilities in multi-processor systems-on-chip (SoCs).We evaluated the proposed architectures in the context of open-source face verification algorithms running on a commercial embedded processor (xt ens a from Tensilica). Our work shows that fast, in-system verification is possible even in the context of many resource-constrained embedded systems. We also demonstrate that high authentication accuracy can be achieved with minimum hardware overheads, while requiring no modifications to the core face verification algorithms.

Magnetic signatures in air for mobile devices

“…This can be especially important for authentication on small mobile devices. Besides, the magnetic interaction does not suffer from illumination and occlusion problems faced by the computer vision based authentication methods such as iris, face recognition [1][2]. In addition, since the proposed approach relies on the magnetic field which can pass through obstructing materials, the interaction can be performed even if the device is not in the line of sight.…”

“…face, iris, and fingerprint) [1][2][3] are recently adopted for mobile devices that can not be shared or copied since they rely on unique physical characteristics of the users. However, such authentication mechanisms can be computationally expensive, suffer from illumination and occlusion problems, and require changes in physical and hardware design of mobile devices.…”

Embedded System for Biometric Identification

“…personal appliances such as cell phones, PDAs, smart card, portable storage devices), or perform safety-critical functions (e.g. automotive and aviation electronics, medical appliances) (Aaraj et al, 2006).…”

Implicit User Re-authentication for Mobile Devices

“…While password based mechanisms are the most used [1], they are insufficient. Therefore some researchers have proposed other techniques that rely on hardware or software enhancements for efficient authentication based on fingerprint [2], face recognition [3], and iris data [8]. Moon et al [7] implemented a Gaussian mixture model based speaker verification module on a mobile system.…”

“…Currently, the most widely used authentication method is explicit authentication, i.e., authentication is performed once at start-up by asking for a password [1], a fingerprint [2], a face profile [3], or a combination. However, all these approaches are intermittent and therefore susceptible to attack, e.g., an unauthorized user can access a portable computer either by stealing a password or exploiting an open account of an authorized user.…”