Robust Machine Vision Framework for localization of unknown objects

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.