FCOS Based Seatbelt Detection System Using Thermal Imaging for Monitoring Traffic Rule Violations

2020 ◽  
Author(s):  
Prashanth Kannadaguli
Keyword(s):  
Thermal Imaging ◽  
Detection System ◽  
Traffic Rule

Obstacle Detection System for Small UAVs using ADS-B and Thermal Imaging

2017 ◽  
Vol 88 (2-4) ◽  
pp. 583-595 ◽  
Author(s):  
Adrian Carrio ◽  
Yucong Lin ◽  
Srikanth Saripalli ◽  
Pascual Campoy
Keyword(s):  
Thermal Imaging ◽  
Detection System ◽  
Obstacle Detection

An Intelligent Thermal Imaging System Adopting Fuzzy-Logic-Based Viola Jones Method in Flu Detection

2017 ◽  
pp. 1-39 ◽  
Author(s):  
Wai Kit Wong ◽  
Nur Izzati Nadiah Binti Ishak ◽  
Heng Siong Lim ◽  
Jalil bin Md Desa
Keyword(s):  
Fuzzy Logic ◽  
Body Temperature ◽  
Thermal Imaging ◽  
Human Subject ◽  
Imaging System ◽  
Detection System ◽  
The Body ◽  
Imaging Tool ◽  
Thermal Imaging System ◽  
Eye Region

Some infectious diseases can spread rapidly via a community of human or animals or both, either through airborne particles or viruses. Such rapid spread diseases may become a local, national or international widespread and contagious threat. As a symptom of infection, the body temperature of a disease carrier is higher than normal people. In this chapter, flu detection system using thermal imaging tool and computer vision techniques are discussed. An automatic flu detection method adopting human object extraction algorithm and fuzzy logic based Viola Jones algorithm are also discussed. The proposed system able to capture a thermogram of the human subject, detecting the eye region of the human subject, calculating the pixels values around the detected eye region, converted to temperature readings and further classified the subject's body temperature whether the subject satisfies a flu condition or not. Experimental results also shown that the proposed fuzzy logic based Viola Jones algorithm can trace out flu infectious personal from the input thermal images up to 80% of accuracy.

scholarly journals Forest Fire Finder – DOAS application to long range forest fire detection

2016 ◽  
Author(s):  
Rui Valente de Almeida ◽  
Pedro Vieira
Keyword(s):  
Forest Fire ◽  
Thermal Imaging ◽  
Imaging System ◽  
Detection System ◽  
Fire Detection ◽  
Spectroscopic Technique ◽  
Optical Absorption Spectroscopy ◽  
Fire Detection System ◽  
Thermal Imaging System ◽  
Forest Fire Detection

Abstract. Fires are an important factor in shaping Earth's ecosystems. Plant and animal life, in almost every land habitat, are at least partially dependant on the effects of fire. However, their destructive force, which many times has proven itself uncontrollable, is one of our greatest concerns, effectively originating several policies in the most important industrialised regions of the globe. This paper aims to comprehensively characterise the Forest Fire Finder (FFF), a forest fire detection system based mainly upon a spectroscopic technique called Differential Optical Absorption Spectroscopy (DOAS). The system is designed and configured with the goal of detecting higher-than-the-horizon smoke columns by measuring and comparing scattered sunlight spectra. The article covers hardware and software, as well as their interactions and specific algorithms for day mode operation. An analysis of data retrieved from several installations deployed in the course of the last five years, is also presented. Finally, this document features a discussion on the most prominent future improvements planned for the system, as well as its ramifications and adaptations, such as a thermal imaging system for short range fire seeking or environmental quality control.

scholarly journals An innovative person detection system based on thermal imaging cameras dedicate for underground belt conveyors

Mining Scince ◽  
2019 ◽  
Vol 26 ◽  
Author(s):  
Fabian Uth ◽  
Bartosz Polnik ◽  
Wojciech Kurpiel ◽  
Ralph Baltes ◽  
Peter Kriegsch ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Underground Mining ◽  
Detection System ◽  
Test Case ◽  
Person Detection ◽  
Long Wavelength ◽  
Safety Improvement ◽  
Coal Rock ◽  
Belt Conveyors ◽  
Transportation Routes

Within the INESI-project (Increasing Efficiency and Safety Improvement in Underground Mining Transportation Routes) long-wavelength infrared (LWIR) cameras are used for detecting persons on underground belt conveyors or within hazardous areas e.g. in front of crusher or skip vessels by the project partners KOMAG and the Institute for Advanced Mining Technologies (AMT). The test case for evaluating the performance of thermal imaging regarding these applications is the Polish Sobieski underground coal mine operated by Tauron mining company. By the development of thermal image processing algorithms, an automated detection of persons and classification of different objects was achieved. This may allow implementing smart services for person detection on underground belt conveyors as well as material characterization between coal, rock and disturbing objects on belt conveyors.

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