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Sensors, Volume 15, Issue 10 (October 2015), Pages 24681-27392

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Open AccessArticle A Low-Cost Modular Platform for Heterogeneous Data Acquisition with Accurate Interchannel Synchronization
Sensors 2015, 15(10), 27374-27392; https://doi.org/10.3390/s151027374
Received: 1 August 2015 / Revised: 11 August 2015 / Accepted: 20 October 2015 / Published: 27 October 2015
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Abstract
Most experimental fields of science and engineering require the use of data acquisition systems (DAQ), devices in charge of sampling and converting electrical signals into digital data and, typically, performing all of the required signal preconditioning. Since commercial DAQ systems are normally focused
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Most experimental fields of science and engineering require the use of data acquisition systems (DAQ), devices in charge of sampling and converting electrical signals into digital data and, typically, performing all of the required signal preconditioning. Since commercial DAQ systems are normally focused on specific types of sensors and actuators, systems engineers may need to employ mutually-incompatible hardware from different manufacturers in applications demanding heterogeneous inputs and outputs, such as small-signal analog inputs, differential quadrature rotatory encoders or variable current outputs. A common undesirable side effect of heterogeneous DAQ hardware is the lack of an accurate synchronization between samples captured by each device. To solve such a problem with low-cost hardware, we present a novel modular DAQ architecture comprising a base board and a set of interchangeable modules. Our main design goal is the ability to sample all sources at predictable, fixed sampling frequencies, with a reduced synchronization mismatch (<1 µs) between heterogeneous signal sources. We present experiments in the field of mechanical engineering, illustrating vibration spectrum analyses from piezoelectric accelerometers and, as a novelty in these kinds of experiments, the spectrum of quadrature encoder signals. Part of the design and software will be publicly released online. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Monolithic CMOS Magnetic Hall Sensor with High Sensitivity and Linearity Characteristics
Sensors 2015, 15(10), 27359-27373; https://doi.org/10.3390/s151027359
Received: 15 September 2015 / Revised: 17 October 2015 / Accepted: 20 October 2015 / Published: 27 October 2015
Cited by 7 | PDF Full-text (1108 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a fully integrated linear Hall sensor by means of 0.8 μm high voltage complementary metal-oxide semiconductor (CMOS) technology. This monolithic Hall sensor chip features a highly sensitive horizontal switched Hall plate and an efficient signal conditioner using dynamic offset cancellation
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This paper presents a fully integrated linear Hall sensor by means of 0.8 μm high voltage complementary metal-oxide semiconductor (CMOS) technology. This monolithic Hall sensor chip features a highly sensitive horizontal switched Hall plate and an efficient signal conditioner using dynamic offset cancellation technique. An improved cross-like Hall plate achieves high magnetic sensitivity and low offset. A new spinning current modulator stabilizes the quiescent output voltage and improves the reliability of the signal conditioner. The tested results show that at the 5 V supply voltage, the maximum Hall output voltage of the monolithic Hall sensor microsystem, is up to ±2.1 V and the linearity of Hall output voltage is higher than 99% in the magnetic flux density range from ±5 mT to ±175 mT. The output equivalent residual offset is 0.48 mT and the static power consumption is 20 mW. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Evaluation of Sensor Configurations for Robotic Surgical Instruments
Sensors 2015, 15(10), 27341-27358; https://doi.org/10.3390/s151027341
Received: 15 May 2015 / Revised: 26 September 2015 / Accepted: 19 October 2015 / Published: 27 October 2015
Cited by 2 | PDF Full-text (4335 KB) | HTML Full-text | XML Full-text
Abstract
Designing surgical instruments for robotic-assisted minimally-invasive surgery (RAMIS) is challenging due to constraints on the number and type of sensors imposed by considerations such as space or the need for sterilization. A new method for evaluating the usability of virtual teleoperated surgical instruments
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Designing surgical instruments for robotic-assisted minimally-invasive surgery (RAMIS) is challenging due to constraints on the number and type of sensors imposed by considerations such as space or the need for sterilization. A new method for evaluating the usability of virtual teleoperated surgical instruments based on virtual sensors is presented. This method uses virtual prototyping of the surgical instrument with a dual physical interaction, which allows testing of different sensor configurations in a real environment. Moreover, the proposed approach has been applied to the evaluation of prototypes of a two-finger grasper for lump detection by remote pinching. In this example, the usability of a set of five different sensor configurations, with a different number of force sensors, is evaluated in terms of quantitative and qualitative measures in clinical experiments with 23 volunteers. As a result, the smallest number of force sensors needed in the surgical instrument that ensures the usability of the device can be determined. The details of the experimental setup are also included. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping
Sensors 2015, 15(10), 27322-27340; https://doi.org/10.3390/s151027322
Received: 31 July 2015 / Revised: 14 October 2015 / Accepted: 19 October 2015 / Published: 27 October 2015
Cited by 8 | PDF Full-text (908 KB) | HTML Full-text | XML Full-text
Abstract
Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area.
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Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Toward a Smartphone Application for Estimation of Pulse Transit Time
Sensors 2015, 15(10), 27303-27321; https://doi.org/10.3390/s151027303
Received: 13 August 2015 / Revised: 17 October 2015 / Accepted: 22 October 2015 / Published: 27 October 2015
Cited by 1 | PDF Full-text (1359 KB) | HTML Full-text | XML Full-text
Abstract
Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras
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Pulse transit time (PTT) is an important physiological parameter that directly correlates with the elasticity and compliance of vascular walls and variations in blood pressure. This paper presents a PTT estimation method based on photoplethysmographic imaging (PPGi). The method utilizes two opposing cameras for simultaneous acquisition of PPGi waveform signals from the index fingertip and the forehead temple. An algorithm for the detection of maxima and minima in PPGi signals was developed, which includes technology for interpolation of the real positions of these points. We compared our PTT measurements with those obtained from the current methodological standards. Statistical results indicate that the PTT measured by our proposed method exhibits a good correlation with the established method. The proposed method is especially suitable for implementation in dual-camera-smartphones, which could facilitate PTT measurement among populations affected by cardiac complications. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Quantification Method for Electrolytic Sensors in Long-Term Monitoring of Ambient Air Quality
Sensors 2015, 15(10), 27283-27302; https://doi.org/10.3390/s151027283
Received: 24 August 2015 / Revised: 16 October 2015 / Accepted: 20 October 2015 / Published: 27 October 2015
Cited by 13 | PDF Full-text (4871 KB) | HTML Full-text | XML Full-text
Abstract
Traditional air quality monitoring relies on point measurements from a small number of high-end devices. The recent growth in low-cost air sensing technology stands to revolutionize the way in which air quality data are collected and utilized. While several technologies have emerged in
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Traditional air quality monitoring relies on point measurements from a small number of high-end devices. The recent growth in low-cost air sensing technology stands to revolutionize the way in which air quality data are collected and utilized. While several technologies have emerged in the field of low-cost monitoring, all suffer from similar challenges in data quality. One technology that shows particular promise is that of electrolytic (also known as amperometric) sensors. These sensors produce an electric current in response to target pollutants. This work addresses the development of practical models for understanding and quantifying the signal response of electrolytic sensors. Such models compensate for confounding effects on the sensor response, such as ambient temperature and humidity, and address other issues that affect the usability of low-cost sensors, such as sensor drift and inter-sensor variability Full article
(This article belongs to the Special Issue Gas Sensors—Designs and Applications)
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Open AccessArticle In-Line Measurement of Water Contents in Ethanol Using a Zeolite-Coated Quartz Crystal Microbalance
Sensors 2015, 15(10), 27273-27282; https://doi.org/10.3390/s151027273
Received: 5 September 2015 / Revised: 22 October 2015 / Accepted: 23 October 2015 / Published: 27 October 2015
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Abstract
A quartz crystal microbalance (QCM) was utilized to measure the water content in ethanol. For the improvement of measurement sensitivity, the QCM was modified by applying zeolite particles on the surface with poly(methyl methacrylate) (PMMA) binder. The measurement performance was examined with ethanol
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A quartz crystal microbalance (QCM) was utilized to measure the water content in ethanol. For the improvement of measurement sensitivity, the QCM was modified by applying zeolite particles on the surface with poly(methyl methacrylate) (PMMA) binder. The measurement performance was examined with ethanol of 1% to 5% water content in circulation. The experimental results showed that the frequency drop of the QCM was related with the water content though there was some deviation. The sensitivity of the zeolite-coated QCM was sufficient to be implemented in water content determination, and a higher ratio of silicon to aluminum in the molecular structure of the zeolite gave better performance. The coated surface was inspected by microscopy to show the distribution of zeolite particles and PMMA spread. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle APFiLoc: An Infrastructure-Free Indoor Localization Method Fusing Smartphone Inertial Sensors, Landmarks and Map Information
Sensors 2015, 15(10), 27251-27272; https://doi.org/10.3390/s151027251
Received: 3 September 2015 / Revised: 19 October 2015 / Accepted: 19 October 2015 / Published: 26 October 2015
Cited by 14 | PDF Full-text (1609 KB) | HTML Full-text | XML Full-text
Abstract
The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on
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The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on infrastructure such as Wi-Fi access points. To address this problem, we propose APFiLoc—a low cost, smartphone-based framework for indoor localization. The key idea behind this framework is to obtain landmarks within the environment and to use the augmented particle filter to fuse them with measurements from smartphone sensors and map information. A clustering method based on distance constraints is developed to detect organic landmarks in an unsupervised way, and the least square support vector machine is used to classify seed landmarks. A series of real-world experiments were conducted in complex environments including multiple floors and the results show APFiLoc can achieve 80% accuracy (phone in the hand) and around 70% accuracy (phone in the pocket) of the error less than 2 m error without the assistance of infrastructure like Wi-Fi access points. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Open AccessArticle Step Detection Robust against the Dynamics of Smartphones
Sensors 2015, 15(10), 27230-27250; https://doi.org/10.3390/s151027230
Received: 4 September 2015 / Revised: 12 October 2015 / Accepted: 22 October 2015 / Published: 26 October 2015
Cited by 13 | PDF Full-text (13123 KB) | HTML Full-text | XML Full-text
Abstract
A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the
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A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Robust Analysis of Network-Based Real-Time Kinematic for GNSS-Derived Heights
Sensors 2015, 15(10), 27215-27229; https://doi.org/10.3390/s151027215
Received: 21 August 2015 / Revised: 20 October 2015 / Accepted: 20 October 2015 / Published: 26 October 2015
Cited by 5 | PDF Full-text (3705 KB) | HTML Full-text | XML Full-text
Abstract
New guidelines and procedures for real-time (RT) network-based solutions are required in order to support Global Navigation Satellite System (GNSS) derived heights. Two kinds of experiments were carried out to analyze the performance of the network-based real-time kinematic (RTK) solutions. New test marks
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New guidelines and procedures for real-time (RT) network-based solutions are required in order to support Global Navigation Satellite System (GNSS) derived heights. Two kinds of experiments were carried out to analyze the performance of the network-based real-time kinematic (RTK) solutions. New test marks were installed in different surrounding environments, and the existing GPS benchmarks were used for analyzing the effect of different factors, such as baseline lengths, antenna types, on the final accuracy and reliability of the height estimation. The RT solutions are categorized into three groups: single-base RTK, multiple-epoch network RTK (mRTN), and single-epoch network RTK (sRTN). The RTK solution can be biased up to 9 mm depending on the surrounding environment, but there was no notable bias for a longer reference base station (about 30 km) In addition, the occupation time for the network RTK was investigated in various cases. There is no explicit bias in the solution for different durations, but smoother results were obtained for longer durations. Further investigation is needed into the effect of changing the occupation time between solutions and into the possibility of using single-epoch solutions in precise determination of heights by GNSS. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
Sensors 2015, 15(10), 27201-27214; https://doi.org/10.3390/s151027201
Received: 30 July 2015 / Revised: 11 October 2015 / Accepted: 22 October 2015 / Published: 26 October 2015
Cited by 5 | PDF Full-text (2733 KB) | HTML Full-text | XML Full-text
Abstract
Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to
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Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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Open AccessArticle Dynamic Strain Measurements on Automotive and Aeronautic Composite Components by Means of Embedded Fiber Bragg Grating Sensors
Sensors 2015, 15(10), 27174-27200; https://doi.org/10.3390/s151027174
Received: 8 September 2015 / Revised: 15 October 2015 / Accepted: 20 October 2015 / Published: 26 October 2015
Cited by 10 | PDF Full-text (6385 KB) | HTML Full-text | XML Full-text
Abstract
The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials
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The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials and serve as in situ sensors. In this article, embedded optical fiber Bragg grating (FBG) sensors are used to analyze the vibration characteristics of two real-life composite components. The first component is a carbon fiber-reinforced polymer automotive control arm; the second is a glass fiber-reinforced polymer aeronautic hinge arm. The modal parameters of both components were estimated by processing the FBG signals with two interrogation techniques: the maximum detection and fast phase correlation algorithms were employed for the demodulation of the FBG signals; the Peak-Picking and PolyMax techniques were instead used for the parameter estimation. To validate the FBG outcomes, reference measurements were performed by means of a laser Doppler vibrometer. The analysis of the results showed that the FBG sensing capabilities were enhanced when the recently-introduced fast phase correlation algorithm was combined with the state-of-the-art PolyMax estimator curve fitting method. In this case, the FBGs provided the most accurate results, i.e., it was possible to fully characterize the vibration behavior of both composite components. When using more traditional interrogation algorithms (maximum detection) and modal parameter estimation techniques (Peak-Picking), some of the modes were not successfully identified. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessReview Interferon (IFN) and Cellular Immune Response Evoked in RNA-Pattern Sensing During Infection with Hepatitis C Virus (HCV)
Sensors 2015, 15(10), 27160-27173; https://doi.org/10.3390/s151027160
Received: 26 May 2015 / Revised: 10 October 2015 / Accepted: 19 October 2015 / Published: 23 October 2015
Cited by 6 | PDF Full-text (872 KB) | HTML Full-text | XML Full-text
Abstract
Hepatitis C virus (HCV) infects hepatocytes but not dendritic cells (DCs), but DCs effectively mature in response to HCV-infected hepatocytes. Using gene-disrupted mice and hydrodynamic injection strategy, we found the MAVS pathway to be crucial for induction of type III interferons (IFNs) in
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Hepatitis C virus (HCV) infects hepatocytes but not dendritic cells (DCs), but DCs effectively mature in response to HCV-infected hepatocytes. Using gene-disrupted mice and hydrodynamic injection strategy, we found the MAVS pathway to be crucial for induction of type III interferons (IFNs) in response to HCV in mouse. Human hepatocytes barely express TLR3 under non-infectious states, but frequently express it in HCV infection. Type I and III IFNs are induced upon stimulation with polyI:C, an analog of double-stranded (ds)RNA. Activation of TLR3 and the TICAM-1 pathway, followed by DC-mediated activation of cellular immunity, is augmented during exposure to viral RNA. Although type III IFNs are released from replication-competent human hepatocytes, DC-mediated CTL proliferation and NK cell activation hardly occur in response to the released type III IFNs. Yet, type I IFNs and HCV-infected hepatocytes can induce maturation of DCs in either human or mouse origin. In addition, mouse CD8+ DCs mature in response to HCV-infected hepatocytes unless the TLR3/TICAM-1 pathway is blocked. We found the exosomes containing HCV RNA in the supernatant of the HCV-infected hepatocytes act as a source of TLR3-mediated DC maturation. Here we summarize our view on the mechanism by which DCs mature to induce NK and CTL in a status of HCV infection. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine
Sensors 2015, 15(10), 27142-27159; https://doi.org/10.3390/s151027142
Received: 16 September 2015 / Revised: 16 October 2015 / Accepted: 16 October 2015 / Published: 23 October 2015
Cited by 4 | PDF Full-text (1638 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the
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In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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Open AccessArticle An Indoor Obstacle Detection System Using Depth Information and Region Growth
Sensors 2015, 15(10), 27116-27141; https://doi.org/10.3390/s151027116
Received: 16 June 2015 / Revised: 14 September 2015 / Accepted: 9 October 2015 / Published: 23 October 2015
Cited by 8 | PDF Full-text (10980 KB) | HTML Full-text | XML Full-text
Abstract
This study proposes an obstacle detection method that uses depth information to allow the visually impaired to avoid obstacles when they move in an unfamiliar environment. The system is composed of three parts: scene detection, obstacle detection and a vocal announcement. This study
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This study proposes an obstacle detection method that uses depth information to allow the visually impaired to avoid obstacles when they move in an unfamiliar environment. The system is composed of three parts: scene detection, obstacle detection and a vocal announcement. This study proposes a new method to remove the ground plane that overcomes the over-segmentation problem. This system addresses the over-segmentation problem by removing the edge and the initial seed position problem for the region growth method using the Connected Component Method (CCM). This system can detect static and dynamic obstacles. The system is simple, robust and efficient. The experimental results show that the proposed system is both robust and convenient. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
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