Applying Optoelectronic Devices Fusion in Machine Vision: Spatial Coordinate Measurement

Applying Optoelectronic Devices Fusion in Machine Vision: Spatial Coordinate Measurement

Wendy Flores-Fuentes, Moises Rivas-Lopez, Daniel Hernandez-Balbuena, Oleg Sergiyenko, Julio C. Rodríguez-Quiñonez, Javier Rivera-Castillo, Lars Lindner, Luis C. Basaca-Preciado
Copyright: © 2017 |Pages: 37
DOI: 10.4018/978-1-5225-0632-4.ch001
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Abstract

Machine vision is supported and enhanced by optoelectronic devices, the output from a machine vision system is information about the content of the optoelectronic signal, it is the process whereby a machine, usually a digital computer and/or electronic hardware automatically processes an optoelectronic signal and reports what it means. Machine vision methods to provide spatial coordinates measurement has developed in a wide range of technologies for multiples fields of applications such as robot navigation, medical scanning, and structural monitoring. Each technology with specified properties that could be categorized as advantage and disadvantage according its utility to the application purpose. This chapter presents the application of optoelectronic devices fusion as the base for those systems with non-lineal behavior supported by artificial intelligence techniques, which require the use of information from various sensors for pattern recognition to produce an enhanced output.
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Background

Optoelectronics is the study of any devices that produce an electrically-induced optical output or an optically-induced electrical output and the techniques for controlling such devices (Marston, 1999), it includes generation, transmission, routing, and detection of optoelectronic signals in a widespread of applications (Dagenais, 1995). Wherever light is used to transmit information, tiny semiconductor devices are needed to transfer electrical current into optical signals and vice versa. Examples include light-emitting diodes, photodetectors and laser diodes (Piprek, 2003).

Most optoelectronics devices applications have focused on single sensors and relatively simple processes to extract specific information from the sensor, however the use of multiple sensors by an optoelectronic device fusion technology deliver more advanced information and enable to develop intelligent and sophisticated optoelectronic systems, in special for machine vision applications (Yallup, 2014). More than one optoelectronic sensor may be needed to fully monitor the observation space at all times. Methods of combining multiple sensor data are in developing due to the availability and computational power of communications devices that support algorithms needed to reduce the raw sensor data from multiple sensors to convert it to the information needed by the system user (Klein, 2003).

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