Open AccessThermographic imaging for use in artificial intelligence and vision algorithms
Author(s) -
Jesús Silva,
Ana María Echeverría,
Noel Varela,
Omar Bonerge Píneda Lezama
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/872/1/012035
Subject(s) - computer science , automation , robotics , artificial intelligence , reliability (semiconductor) , image processing , computer vision , pixel , image (mathematics) , engineering , robot , mechanical engineering , power (physics) , physics , quantum mechanics
The constant technological innovation in devices for the acquisition of digital images such as: energy-efficient and high-pixel sensors, memories with greater storage capacity and processors capable of sampling digital signals more quickly, have made it possible to digitize with greater reliability real life scenes in an instant of time, making it possible to analyze and interpret different physical phenomena [1][2][3] such as fractures in materials, evasion of obstacles, weather conditions, injury detection, among others, giving rise to a new line of research called Artificial Vision (AV) focused on generating algorithms to improve image quality, segment characteristics of interest and eventually recognize patterns, in order to make more efficient image processing for the solution of problems in robotics, automation, security, medicine, veterinary, and others. The research aims to develop a database of thermographic images of pregnant and non-pregnant sheep, providing a tool for specialists in the area of computer intelligence and artificial vision.