scholarly journals Detecting Small Size and Minimal Thermal Signature Targets in Infrared Imagery Using Biologically Inspired Vision

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1812
Author(s):  
Muhammad Uzair ◽  
Russell S. A. Brinkworth ◽  
Anthony Finn
Keyword(s):  
Moving Objects ◽  
Infrared Imaging ◽  
Infrared Image ◽  
Detection Methods ◽  
Biologically Inspired ◽  
Insect Visual System ◽  
Thermal Infrared Imaging ◽  
Spatio Temporal ◽  
Thermal Signature ◽  
Two Stages

Thermal infrared imaging provides an effective sensing modality for detecting small moving objects at long range. Typical challenges that limit the efficiency and robustness of the detection performance include sensor noise, minimal target contrast and cluttered backgrounds. These issues become more challenging when the targets are of small physical size and present minimal thermal signatures. In this paper, we experimentally show that a four-stage biologically inspired vision (BIV) model of the flying insect visual system have an excellent ability to overcome these challenges simultaneously. The early two stages of the model suppress spatio-temporal clutter and enhance spatial target contrast while compressing the signal in a computationally manageable bandwidth. The later two stages provide target motion enhancement and sub-pixel motion detection capabilities. To show the superiority of the BIV target detector over existing traditional detection methods, we perform extensive experiments and performance comparisons using high bit-depth, real-world infrared image sequences of small size and minimal thermal signature targets at long ranges. Our results show that the BIV target detector significantly outperformed 10 conventional spatial-only and spatiotemporal methods for infrared small target detection. The BIV target detector resulted in over 25 dB improvement in the median signal-to-clutter-ratio over the raw input and achieved 43% better detection rate than the best performing existing method.

scholarly journals Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission

2019 ◽  
Vol 11 (10) ◽  
pp. 1251 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Infrared Imaging ◽  
Thermal Infrared ◽  
Resource Assessment ◽  
Regression Kriging ◽  
Scale Invariant ◽  
Thermal Infrared Imaging ◽  
Spatio Temporal ◽  
Classification Index

This work is linked to the future Indian–French high spatio-temporal TRISHNA (Thermal infraRed Imaging Satellite for High-resolution natural resource Assessment) mission, which includes shortwave and thermal infrared bands, and is devoted amongst other things to the monitoring of urban heat island events. In this article, the performance of seven empirical thermal unmixing techniques applied on simulated TRISHNA satellite images of an urban scenario is studied across spatial resolutions. For this purpose, Top Of Atmosphere (TOA) images in the shortwave and Thermal InfraRed (TIR) ranges are constructed at different resolutions (20 m, 40 m, 60 m, 80 m, and 100 m) and according to TRISHNA specifications (spectral bands and sensor properties). These images are synthesized by correcting and undersampling DESIREX 2008 Airborne Hyperspectral Scanner (AHS) images of Madrid at 4 m resolution. This allows to compare the Land Surface Temperature (LST) retrieval of several unmixing techniques applied on different resolution images, as well as to characterize the evolution of the performance of each technique across resolutions. The seven unmixing techniques are: Disaggregation of radiometric surface Temperature (DisTrad), Thermal imagery sHARPening (TsHARP), Area-To-Point Regression Kriging (ATPRK), Adaptive Area-To-Point Regression Kriging (AATPRK), Urban Thermal Sharpener (HUTS), Multiple Linear Regressions (MLR), and two combinations of ground classification (index-based classification and K-means classification) with DisTrad. Studying these unmixing techniques across resolutions also allows to validate the scale invariance hypotheses on which the techniques hinge. Each thermal unmixing technique has been tested with several shortwave indices, in order to choose the best one. It is shown that (i) ATPRK outperforms the other compared techniques when characterizing the LST of Madrid, (ii) the unmixing performance of any technique is degraded when the coarse spatial resolution increases, (iii) the used shortwave index does not strongly influence the unmixing performance, and (iv) even if the scale-invariant hypotheses behind these techniques remain empirical, this does not affect the unmixing performances within this range of resolutions.

Application of Passive Thermal Infrared Imaging to Study Ice and Snow Accretion on Automobiles in Cold Regions

2013 ◽  
Vol 739 ◽  
pp. 481-485
Author(s):  
S. Virk Muhammad
Keyword(s):  
Image Processing ◽  
Infrared Imaging ◽  
Infrared Image ◽  
Field Measurements ◽  
Thermal Infrared ◽  
Cold Regions ◽  
Vehicle Performance ◽  
Safe Driving ◽  
Thermal Infrared Imaging ◽  
Infrared Image Processing

The resultant effect of ice and snow accretion on automobiles in cold regions may induce performance losses by provoking mechanical system failures and structural damages. Different methods for ice/snow detection and measurement have been used by researchers, ranging from simple monitoring techniques to advanced complex ones. Thermal infrared image processing based techniques can be a promising way for ice and snow detection on different surface of automobiles in cold regions, but have not extensively been studied so far. This paper presents a preliminary study about application of thermal infrared image processing based techniques for ice and snow detection on various automobiles in cold regions. Preliminary field measurements have been carried out by researchers of Narvik University College in northern part of Norway during winter 2012-2013, where results have shown a potential in this technique. Better knowledge of vehicle performance in icy conditions will help the designers to improve safe driving conditions.

Use of thermal infrared imaging for monitoring renewed dome growth at Mount St. Helens, 2004

2008 ◽  
pp. 347-359 ◽  
Author(s):  
David J. Schneider ◽  
James W. Vallance ◽  
Rick L. Wessels ◽  
Matthew Logan ◽  
Michael S. Ramsey
Keyword(s):  
Infrared Imaging ◽  
Thermal Infrared ◽  
Thermal Infrared Imaging ◽  
Dome Growth ◽  
Mount St Helens

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

Experimental Research to Evaluate Thermal Behavior of a Brushless Driving Servomotor for Linear Motion NC Axis Experimental Stand

2015 ◽  
Vol 762 ◽  
pp. 55-60
Author(s):  
Georgia Cezara Avram ◽  
Florin Adrian Nicolescu ◽  
Radu Constantin Parpală ◽  
Constantin Dumitrascu
Keyword(s):  
Thermal Behavior ◽  
Mathematical Models ◽  
Experimental Research ◽  
Infrared Imaging ◽  
Experimental Results ◽  
Ball Screw ◽  
Linear Motion ◽  
Functional Optimization ◽  
Thermal Infrared Imaging ◽  
Experimental Stand

This paper presents the works carried out by the authors in the field of structural and functional optimization of industrial robot's numerically controlled (NC) axes. The study includes the results obtained in the research stage of the experimental measurements performed to evaluate the electrical servomotor's thermal behavior using a thermal (infrared) imaging camera. The analyzed servomotor is a brushless servomotor integrated in an experimental stand for linear motion NC axis experimental research, existing in the MMS department from EMTS faculty. Supplementary to the driving servomotor, the experimental stand includes a belt drive transmission, a ball screw - bearings assembly and a driven element guided by ball rail system. This experimental research phase is part of the doctoral thesis of first author and was conducted in order to validate the mathematical models developed in the PhD thesis. Thus, experimental results presented in the paper have been used to validate first mathematical models for electric motor's preliminary selection and checking, (performed by determining the total reflected inertia of the mechanical system on motor shaft level) as well as the mathematical models for final selection and checking (by evaluating the servomotor's thermal energy dissipation, and servomotor's internal and external maximum operating temperature). Second, the experimental results have been used to validate the assisted simulation for structural and functional optimization of industrial robot's NC axes based on both servomotor and drive's thermal behavior analysis, performed in the thesis by means of a dedicated commercial software package.

scholarly journals Fabrication of Lignin-Based Nano Carbon Film-Copper Foil Composite with Enhanced Thermal Conductivity

Nanomaterials ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1681 ◽  
Author(s):  
Bin Luo ◽  
Mingchao Chi ◽  
Qingtong Zhang ◽  
Mingfu Li ◽  
Changzhou Chen ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Thermal Management ◽  
Copper Foil ◽  
Infrared Imaging ◽  
Carbon Film ◽  
Composite Films ◽  
Annealing Treatment ◽  
Thermal Infrared Imaging ◽  
Nano Carbon ◽  
Enhanced Thermal Conductivity

Technical lignin from pulping, an aromatic polymer with ~59% carbon content, was employed to develop novel lignin-based nano carbon thin film (LCF)-copper foil composite films for thermal management applications. A highly graphitized, nanoscale LCF (~80–100 nm in thickness) was successfully deposited on both sides of copper foil by spin coating followed by annealing treatment at 1000 °C in an argon atmosphere. The conditions of annealing significantly impacted the morphology and graphitization of LCF and the thermal conductivity of LCF-copper foil composite films. The LCF-modified copper foil exhibited an enhanced thermal conductivity of 478 W m−1 K−1 at 333 K, which was 43% higher than the copper foil counterpart. The enhanced thermal conductivity of the composite films compared with that of the copper foil was characterized by thermal infrared imaging. The thermal properties of the copper foil enhanced by LCF reveals its potential applications in the thermal management of advanced electronic products and highlights the potential high-value utility of lignin, the waste of pulping.

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