Measurement in Machine Vision Editorial Paper

Publikation: Beiträge in ZeitschriftenAndere (Vorworte. Editoral u.ä.)Forschung

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Measurement in Machine Vision Editorial Paper. / Sergiyenko, Oleg; Flores-Fuentes, Wendy; Rodríguez-Quiñonez, Julio C. et al.
in: Measurement: Journal of the International Measurement Confederation, Jahrgang 236, 15.08.2024.

Publikation: Beiträge in ZeitschriftenAndere (Vorworte. Editoral u.ä.)Forschung

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APA

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Sergiyenko O, Flores-Fuentes W, Rodríguez-Quiñonez JC, Mercorelli P, Kawabe T, Bhateja V. Measurement in Machine Vision Editorial Paper. Measurement: Journal of the International Measurement Confederation. 2024 Aug 15;236. doi: 10.1016/j.measurement.2023.114062

Bibtex

@article{4bd88dcb82d349d1a5dda7fbbf29c2b9,
title = "Measurement in Machine Vision Editorial Paper",
abstract = "Measurement related to different machine vision functions is the base for developing of cyber-physical systems able to see and make decisions. These kinds of systems are emerging in all areas of our daily lives. They can be found in the medical area, in industry, in the agriculture, in all those interconnected cloud computing-based systems related to flying/terrestrial robotics, navigation, automated surgery, smart cities, smart health monitoring, etc. All of them are extremely dependent on the same: adequate coordinates measurement, properly selected data processing and data fusion algorithms, evaluation procedures for performance analysis of measurement within Machine Vision systems, processes and algorithms (both traditional and artificial intelligence), mathematical models for 3D-measurement purposes (measurement of displacements, surface profiles, deformations, data augmentation/interpolation, etc.), and distributed visual measurement systems, as well as distributed memory and sensory part. Cyber-physical systems can be implemented on almost any application, especially on those dotted by robots and automated guided devices (from aerospace applications to domestic cleaners). The success of the measurement process depends on the kind of sensors and their optoelectronics characteristics and intrinsic parameters, as well as their respective operating and processing. The correct approach selection for the application, the data acquisition and collection efficiency, the data processing algorithms, the hardware processors response time, and the intelligent auto adaptability to changing environments or conditions. Recently, the emergence of artificial intelligence algorithms and the internet of things have powerful development of such systems, highlighting the importance and the impact of the measurement accuracy related to machine vision performance.",
keywords = "3D Spatial Coordinates, Artificial Intelligence, Automatic Measurements, Machine Vision, Measurement, Optical Computing, Remote Sensing, Technical Vision Systems, Engineering",
author = "Oleg Sergiyenko and Wendy Flores-Fuentes and Rodr{\'i}guez-Qui{\~n}onez, {Julio C.} and Paolo Mercorelli and Tohru Kawabe and Vikrant Bhateja",
note = "Publisher Copyright: {\textcopyright} 2023",
year = "2024",
month = aug,
day = "15",
doi = "10.1016/j.measurement.2023.114062",
language = "English",
volume = "236",
journal = "Measurement: Journal of the International Measurement Confederation",
issn = "0263-2241",
publisher = "Elsevier B.V.",

}

RIS

TY - JOUR

T1 - Measurement in Machine Vision Editorial Paper

AU - Sergiyenko, Oleg

AU - Flores-Fuentes, Wendy

AU - Rodríguez-Quiñonez, Julio C.

AU - Mercorelli, Paolo

AU - Kawabe, Tohru

AU - Bhateja, Vikrant

N1 - Publisher Copyright: © 2023

PY - 2024/8/15

Y1 - 2024/8/15

N2 - Measurement related to different machine vision functions is the base for developing of cyber-physical systems able to see and make decisions. These kinds of systems are emerging in all areas of our daily lives. They can be found in the medical area, in industry, in the agriculture, in all those interconnected cloud computing-based systems related to flying/terrestrial robotics, navigation, automated surgery, smart cities, smart health monitoring, etc. All of them are extremely dependent on the same: adequate coordinates measurement, properly selected data processing and data fusion algorithms, evaluation procedures for performance analysis of measurement within Machine Vision systems, processes and algorithms (both traditional and artificial intelligence), mathematical models for 3D-measurement purposes (measurement of displacements, surface profiles, deformations, data augmentation/interpolation, etc.), and distributed visual measurement systems, as well as distributed memory and sensory part. Cyber-physical systems can be implemented on almost any application, especially on those dotted by robots and automated guided devices (from aerospace applications to domestic cleaners). The success of the measurement process depends on the kind of sensors and their optoelectronics characteristics and intrinsic parameters, as well as their respective operating and processing. The correct approach selection for the application, the data acquisition and collection efficiency, the data processing algorithms, the hardware processors response time, and the intelligent auto adaptability to changing environments or conditions. Recently, the emergence of artificial intelligence algorithms and the internet of things have powerful development of such systems, highlighting the importance and the impact of the measurement accuracy related to machine vision performance.

AB - Measurement related to different machine vision functions is the base for developing of cyber-physical systems able to see and make decisions. These kinds of systems are emerging in all areas of our daily lives. They can be found in the medical area, in industry, in the agriculture, in all those interconnected cloud computing-based systems related to flying/terrestrial robotics, navigation, automated surgery, smart cities, smart health monitoring, etc. All of them are extremely dependent on the same: adequate coordinates measurement, properly selected data processing and data fusion algorithms, evaluation procedures for performance analysis of measurement within Machine Vision systems, processes and algorithms (both traditional and artificial intelligence), mathematical models for 3D-measurement purposes (measurement of displacements, surface profiles, deformations, data augmentation/interpolation, etc.), and distributed visual measurement systems, as well as distributed memory and sensory part. Cyber-physical systems can be implemented on almost any application, especially on those dotted by robots and automated guided devices (from aerospace applications to domestic cleaners). The success of the measurement process depends on the kind of sensors and their optoelectronics characteristics and intrinsic parameters, as well as their respective operating and processing. The correct approach selection for the application, the data acquisition and collection efficiency, the data processing algorithms, the hardware processors response time, and the intelligent auto adaptability to changing environments or conditions. Recently, the emergence of artificial intelligence algorithms and the internet of things have powerful development of such systems, highlighting the importance and the impact of the measurement accuracy related to machine vision performance.

KW - 3D Spatial Coordinates

KW - Artificial Intelligence

KW - Automatic Measurements

KW - Machine Vision

KW - Measurement

KW - Optical Computing

KW - Remote Sensing

KW - Technical Vision Systems

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85197097473&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/c6cfd7f6-4280-357f-9922-3ea82afb268e/

U2 - 10.1016/j.measurement.2023.114062

DO - 10.1016/j.measurement.2023.114062

M3 - Other (editorial matter etc.)

AN - SCOPUS:85197097473

VL - 236

JO - Measurement: Journal of the International Measurement Confederation

JF - Measurement: Journal of the International Measurement Confederation

SN - 0263-2241

ER -

DOI

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