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Publication
Adaptive image pre-processing for quality control in production lines
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Advisor(s)
Abstract(s)
Flexible and self-adaptive behaviours in automated
quality control systems are features that may significantly
enhance the robustness, efficiency and flexibility of the industrial
production processes. However, most current approaches on
automated quality control are based on rigid inspection methods
and are not capable of accommodating to disturbances affecting
the image acquisition quality, fact that hast direct consequences
on the system´s reliability and performance. In an effort to
address the problem, this paper presents the development of a
self-adaptive software system designed for the pre-processing
(quality enhancement) of digital images captured in industrial
production lines. The approach introduces the use of scene
recognition as a key-feature to allow the execution of customized
image pre-processing strategies, increase the system’s flexibility
and enable self-adapting conducts. Real images captured in a
washing machines production line are presented to test and
validate the system performance. Experimental results
demonstrate significant image quality enhancements and a
valuable reliability improvement of the automated quality
control procedures.
Description
Keywords
Adaptive systems Image pre-processing Industrial quality control Scene recognition
Citation
Arroyo, Esteban; Lima, José; Leitão, Paulo (2013). Adaptive image pre-processing for quality control in production lines. In IEEE International Conference on Industrial Technology. Cape Town: IEEE. p. 1044-1050. ISBN 978-1-4673-4568-2