Authors:
Andrei Hossu
and
Daniela Hossu
Affiliation:
University Politehnica of Bucharest, Faculty of Control and Computers, Romania
Keyword(s):
Vision systems, Gray level image binarization, gray level histogram, global optimum thresholding, dynamic optimum threshold, temporal histogram, temporal thresholding and moving scene in robotic automation.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
This paper presents some aspects of the (gray level) image binarization methods used in artificial vision systems. It is introduced a new approach of gray level image binarization for artificial vision systems dedicated to the specific class of applications for moving scene in industrial automation – temporal thresholding. In the first part of the paper are remarked some limitations of using the global optimum thresholding in gray level image binarization. In the second part of this paper are presented some aspects of the dynamic optimum thresholding method for gray level image binarization. In the third section are introduced the concepts of temporal histogram and temporal thresholding, starting from classic methods of global and dynamic optimal thresholding of the gray level images. In the final part are presented some practical aspects of the temporal thresholding method in artificial vision applications for the moving scene in robotic automation class; highlighting the influence
of the acquisition frequency on the methods results.
(More)