scholarly journals Applying OCR in the Processing of Thermal Images with Temperature Scales

10.5772/51475 ◽  
2012 ◽  
Author(s):  
W.T. Chan ◽  
T.Y. Lo ◽  
C.P. Tso ◽  
K.S. Sim
Keyword(s):  
Thermal Images ◽  
Temperature Scales

Automatic Bruise Detection in Fruits Using Thermal Images

2017 ◽  
Vol 7 (5) ◽  
pp. 727-732 ◽  
Author(s):  
Manisha Satone ◽  
◽  
Samruddhi Diwakar ◽  
Vaishnavi Joshi ◽  
◽  
...  
Keyword(s):  
Thermal Images

ALGORITHMS OF TWO-STAGE RECOVERY OF RADIO THERMAL IMAGES

2017 ◽  
Vol 59 (1) ◽  
pp. 3-9
Author(s):  
V. K. Klochko ◽  
◽  
S. M. Gudkov ◽  
Keyword(s):  
Two Stage ◽  
Thermal Images

Temperature and its measurement

2017 ◽  
Author(s):  
Andrew Clarke
Keyword(s):  
Thermal Equilibrium ◽  
Isotope Fractionation ◽  
Thermodynamic Temperature ◽  
The Other ◽  
Deterministic Models ◽  
Triple Point Of Water ◽  
Temperature Scales ◽  
Classical Thermodynamics ◽  
The Relationship ◽  
Unit Of Temperature

Temperature is that property of a body which determines whether it gains or loses energy in a particular environment. In classical thermodynamics temperature is defined by the relationship between energy and entropy. Temperature can be defined only for a body that is in thermodynamic and thermal equilibrium; whilst organisms do not conform to these criteria, the errors in assuming that they do are generally small. The Celsius and Fahrenheit temperature scales are arbitrary because they require two fixed points, one to define the zero and the other to set the scale. The thermodynamic (absolute) scale of temperature has a natural zero (absolute zero) and is defined by the triple point of water. Its unit of temperature is the Kelvin. The Celsius scale is convenient for much ecological and physiological work, but where temperature is included in statistical or deterministic models, only thermodynamic temperature should be used. Past temperatures can only be reconstructed with the use of proxies, the most important of which are based on isotope fractionation.

Evaluation of the heat changes in an ancient church because of restoration works: A microclimatic study supported by thermal images

2021 ◽  
pp. 1420326X2199462
Author(s):  
Stefano Ridolfi ◽  
Susanna Crescenzi ◽  
Fabiana Zeli ◽  
Stefano Perilli ◽  
Stefano Sfarra
Keyword(s):  
Methodological Approach ◽  
Thermal Capacity ◽  
Outdoor Environment ◽  
Heat Index ◽  
Heat Sources ◽  
Thermal Images ◽  
Roof Structure ◽  
Period 2 ◽  
Microclimate Monitoring ◽  
The Church

This work is centred on an ancient Italian church. Since 2011, a restoration plan has been undertaken by following sequential phases. The methodological approach to restoration was guided by environmental monitoring campaigns. In particular, two thermo-hygrometric campaigns were carried out during the warm months of the years 2015 and 2016. The first set of measurements was executed during the restoration of facades and roofs, making it possible to reach even areas that are usually difficult to access. The second set was performed to evaluate the indoor thermo-hygrometric conditions following the work of the previous year. This was intended to assess their differences in variability, the influence of the outdoor environment and any real and perceived improvement. Results demonstrate that thermal images helped in identifying both the heat sources causing thermal discomforts and the good thermal capacity of masonries. Concerning the heat index (HI), the church showed an improvement in the trend of malaise perceived by people during the second summer period (∼2°C lower than 2015). Finally, in the last microclimate monitoring, the roof structure no longer acted as an amplifier for daily temperature excursions.

scholarly journals Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 988
Author(s):  
Kshirasagar Naik ◽  
Tejas Pandit ◽  
Nitin Naik ◽  
Parth Shah
Keyword(s):  
Internet Of Things ◽  
Activity Recognition ◽  
Thermal Model ◽  
Thermal Image ◽  
Heat Radiation ◽  
Household Activity ◽  
Thermal Images ◽  
Gas Leakage ◽  
3D Space ◽  
Image Pairs

In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces.

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