A Study on Sensor Integration System. 3rd Report. Sensor Integration System with Image Processing and Displacement Sensor.

doi:https://doi.org/10.1299/kikaic.58.3271

Open AccessArticle10.1299/kikaic.58.3271

A Study on Sensor Integration System. 3rd Report. Sensor Integration System with Image Processing and Displacement Sensor.

Koji Shimojima,Toshio Fukuda,Fumihito Arai,Hideo Matsuura,Akira Takeishi,Toshiyuki OOKA-1992-01-01-TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C

0PDF

TL;DRAbstract

This paper deals with a new integrated measurement method for application to a curved metal surface cutting system based on fuzzy inference. This system can recognize a measuring point on the object. This measurement system has two LED displacement sensors and two CCD cameras. The LED displacement sensor's spotlight is used for the active stereo sensing method. In addition, the LED displacement sensor's outputs are used for calibrating camera parameters. Therefore, we can calibrate the camera parameters easily. Then, we use neural networks to compensate the output of image processing for some errors, such as camera parameter error and lens distortion. By utilizing the neural networks, we can use as precise an image processing measurement system as possible. We use a multi-sensor integration system based on the fuzzy set theory. Fuzzy inference's input consists of information on the change in sensor output and the position change of the sensor system, together with the environmental dat

Chat with Paper

AI Agents for this Paper

This paper deals with a new integrated measurement method for application to a curved metal surface cutting system based on fuzzy inference. This system can recognize a measuring point on the object. This measurement system has two LED displacement sensors and two CCD cameras. The LED displacement sensor's spotlight is used for the active stereo sensing method. In addition, the LED displacement sensor's outputs are used for calibrating camera parameters. Therefore, we can calibrate the camera parameters easily. Then, we use neural networks to compensate the output of image processing for some errors, such as camera parameter error and lens distortion. By utilizing the neural networks, we can use as precise an image processing measurement system as possible. We use a multi-sensor integration system based on the fuzzy set theory. Fuzzy inference's input consists of information on the change in sensor output and the position change of the sensor system, together with the environmental dat

Keywords

Computer visionArtificial intelligenceDisplacement (psychology)Computer scienceImage sensorVisual sensor networkDistortion (music)Position (finance)

Chat

Click to start Chat