Authors:
Patrick Waibel
;
Jörg Matthes
and
Hubert Keller
Affiliation:
Karlsruhe Institute of Technology, Germany
Keyword(s):
Rotary kiln, Solid bed, Segmentation, Infrared camera.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Environmental Monitoring and Control
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Vision, Recognition and Reconstruction
Abstract:
This paper presents two novel methods for segmenting the solid bed in infrared image sequences of metalrecycling rotary kilns. Exploiting the different dynamics and temperatures of gas phase, solid bed and kiln wall, we developed filter chains for an image segmentation of the solid bed. For the image acquisition we employed infrared cameras with a spectral filter. Two image processing algorithms were realized according to the two most common camera positions (frontal and top-left view on the solid bed at the rear-end of the kiln). Results show that both algorithms are capable to segment the solid bed in the image sequences accurately and reliably. The work presented here provides a basis for the extraction of characteristic process state variables, that can help to improve the process control with regard to product quality, energy consumption and emission reduction.