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182 KiB

Open AccessArticle

Integrating Iris and Signature Traits for Personal Authentication Using User-SpecificWeighting

by Serestina Viriri and Jules R. Tapamo

Sensors 2012, 12(4), 4324-4338; https://doi.org/10.3390/s120404324 - 29 Mar 2012

Cited by 18 | Viewed by 6736

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this [...] Read more.

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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811 KiB

Open AccessArticle

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

by Angel Jimenez-Fernandez, Gabriel Jimenez-Moreno, Alejandro Linares-Barranco, Manuel J. Dominguez-Morales, Rafael Paz-Vicente and Anton Civit-Balcells

Sensors 2012, 12(4), 3831-3856; https://doi.org/10.3390/s120403831 - 26 Mar 2012

Cited by 59 | Viewed by 11298

Abstract

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be [...] Read more.

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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2070 KiB

Open AccessArticle

Electrical Model of a Carbon-Polymer Composite (CPC) Collision Detector

by Karl Kruusamäe, Andres Punning and Alvo Aabloo

Sensors 2012, 12(2), 1950-1966; https://doi.org/10.3390/s120201950 - 10 Feb 2012

Cited by 11 | Viewed by 8075

Abstract

We present a study of an electrical model of electromechanically active carbon-polymer composite (CPC) with carbide-derived carbon (CDC) electrodes. The major focus is on investigation of surface electrode behavior upon external bending of the material. We show that electrical impedance measured from the [...] Read more.

We present a study of an electrical model of electromechanically active carbon-polymer composite (CPC) with carbide-derived carbon (CDC) electrodes. The major focus is on investigation of surface electrode behavior upon external bending of the material. We show that electrical impedance measured from the surface of the CDC-based CPC can be used to determine the curvature of the material and, hence, the tip displacement of a CPC laminate in a cantilever configuration. It is also shown that by measuring surface signals in the process of an actuator’s work-cycle, we obtain a self-sensing collision-detecting CPC actuator that can be considered as a counterpart of biomimetic vibrissae. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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1720 KiB

Open AccessArticle

Online Assessment of Human-Robot Interaction for Hybrid Control of Walking

by Antonio J. Del-Ama, Juan C. Moreno, Ángel Gil-Agudo, Ana De-los-Reyes and José L. Pons

Sensors 2012, 12(1), 215-225; https://doi.org/10.3390/s120100215 - 27 Dec 2011

Cited by 31 | Viewed by 11459

Abstract

Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid) approach has the potential to provide a solution to the drawback of [...] Read more.

Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid) approach has the potential to provide a solution to the drawback of each approach. Specific challenges must be addressed with specific sensory systems and control strategies. In this paper we present a system and a procedure to estimate muscle fatigue from online physical interaction assessment to provide hybrid control of walking, regarding the performances of the muscles under stimulation. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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26810 KiB

Open AccessArticle

On the Biomimetic Design of Agile-Robot Legs

by Elena Garcia, Juan Carlos Arevalo, Gustavo Muñoz and Pablo Gonzalez-de-Santos

Sensors 2011, 11(12), 11305-11334; https://doi.org/10.3390/s111211305 - 28 Nov 2011

Cited by 41 | Viewed by 37420

Abstract

The development of functional legged robots has encountered its limits in human-made actuation technology. This paper describes research on the biomimetic design of legs for agile quadrupeds. A biomimetic leg concept that extracts key principles from horse legs which are responsible for the [...] Read more.

The development of functional legged robots has encountered its limits in human-made actuation technology. This paper describes research on the biomimetic design of legs for agile quadrupeds. A biomimetic leg concept that extracts key principles from horse legs which are responsible for the agile and powerful locomotion of these animals is presented. The proposed biomimetic leg model defines the effective leg length, leg kinematics, limb mass distribution, actuator power, and elastic energy recovery as determinants of agile locomotion, and values for these five key elements are given. The transfer of the extracted principles to technological instantiations is analyzed in detail, considering the availability of current materials, structures and actuators. A real leg prototype has been developed following the biomimetic leg concept proposed. The actuation system is based on the hybrid use of series elasticity and magneto-rheological dampers which provides variable compliance for natural motion. From the experimental evaluation of this prototype, conclusions on the current technological barriers to achieve real functional legged robots to walk dynamically in agile locomotion are presented. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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2383 KiB

Open AccessArticle

Selective Change Driven Imaging: A Biomimetic Visual Sensing Strategy

by Jose A. Boluda, Pedro Zuccarello, Fernando Pardo and Francisco Vegara

Sensors 2011, 11(11), 11000-11020; https://doi.org/10.3390/s111111000 - 23 Nov 2011

Cited by 8 | Viewed by 7409

Abstract

Selective Change Driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, the [...] Read more.

Selective Change Driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, the pixels that have changed after the last time they were read out. Moreover, the traditional full frame processing hardware and programming methodology has to be changed, as a part of this biomimetic approach, to a new processing paradigm based on pixel processing in a data flow manner, instead of full frame image processing. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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443 KiB

Open AccessArticle

Artificial Skin Ridges Enhance Local Tactile Shape Discrimination

by Saba Salehi, John-John Cabibihan and Shuzhi Sam Ge

Sensors 2011, 11(9), 8626-8642; https://doi.org/10.3390/s110908626 - 5 Sep 2011

Cited by 35 | Viewed by 9815

Abstract

One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the curvature [...] Read more.

One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the curvature detection of embedded tactile sensors by proposing a ridged fingertip structure, simulating human fingerprints. In addition, a curvature detection approach based on machine learning methods is proposed to provide the embedded sensors with the ability to discriminate the surface curvature of different objects. For this purpose, a set of experiments were carried out to collect tactile signals from a 2 × 2 tactile sensor array, then the signals were processed and used for learning algorithms. To achieve the best possible performance for our machine learning approach, three different learning algorithms of Naïve Bayes (NB), Artificial Neural Networks (ANN), and Support Vector Machines (SVM) were implemented and compared for various parameters. Finally, the most accurate method was selected to evaluate the proposed skin structure in recognition of three different curvatures. The results showed an accuracy rate of 97.5% in surface curvature discrimination. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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2868 KiB

Open AccessArticle

An Efficient Direction Field-Based Method for the Detection of Fasteners on High-Speed Railways

by Jinfeng Yang, Wei Tao, Manhua Liu, Yongjie Zhang, Haibo Zhang and Hui Zhao

Sensors 2011, 11(8), 7364-7381; https://doi.org/10.3390/s110807364 - 25 Jul 2011

Cited by 91 | Viewed by 9328

Abstract

Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of image [...] Read more.

Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of image processing and pattern recognition techniques, which can be used to detect the absence of fasteners on the corresponding track in high-speed(up to 400 km/h). The Direction Field is extracted as the feature descriptor for recognition. In addition, the appropriate weight coefficient matrix is presented for robust and rapid matching in a complex environment. Experimental results are presented to show that the proposed method is computation efficient and robust for the detection of fasteners in a complex environment. Through the practical device fixed on the track inspection train, enough fastener samples are obtained, and the feasibility of the method is verified at 400 km/h. Full article

(This article belongs to the Special Issue Biomimetic Sensors, Actuators and Integrated Systems)

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