Title :
Robust Machine Vision Framework for localization of unknown objects
Author :
Grigorescu, S.M. ; Graser, A.
Author_Institution :
Inst. of Autom., Univ. of Bremen, Bremen
Abstract :
In this paper an approach to the detection of unknown objects is presented. The proposed algorithm is applied to the rehabilitation robot FRIEND II for the localization of objects situated in complex scenes. Also, the method was designed to cope with changes in the illumination conditions. The approach used in this work is the inclusion of feedback control in the image processing chain used by the Machine Vision Framework of the robot. A closed-loop control system was designed at image segmentation level for improving the robustness and reliability of the feature extraction module. The design of the closed-loop is based on an Extremum Searching Algorithm which searches for the optimal parameters of the image segmentation method. The performance of the proposed framework is investigated in comparison with a traditional open-loop method.
Keywords :
closed loop systems; feature extraction; feedback; image segmentation; medical robotics; object detection; open loop systems; robot vision; robust control; search problems; closed-loop control system; extremum searching algorithm; feature extraction; feedback control; image processing chain; image segmentation; object detection; open-loop method; rehabilitation robot; robust machine vision framework; Design methodology; Feedback control; Image processing; Image segmentation; Layout; Lighting; Machine vision; Object detection; Rehabilitation robotics; Robustness;
Conference_Titel :
Optimization of Electrical and Electronic Equipment, 2008. OPTIM 2008. 11th International Conference on
Conference_Location :
Brasov
Print_ISBN :
978-1-4244-1544-1
Electronic_ISBN :
978-1-4244-1545-8
DOI :
10.1109/OPTIM.2008.4602468