For further information, please contact the General chair: Pierre-Emmanuel Gaillardon
Professor at Osaka University, Japan
An Efficient Parts Counting Method based on Intensity Distribution Analysis for Industrial Vision Systems
Counting productions, as a preliminary operation in assemble line, is essential for calculating many industrial index such as deficiency rate. Conventional approach for counting problem is based on template matching, which we consider it as both stiff and time-consuming. In the proposed approach, counting problem is converted into an equivalent classification problem, in which a trained classifier is used to classify whether a specific line segment region belongs to parts or not. While parts flow through this line segment, number of the flowed parts can be effectively counted according to the interlace of different classification results. Experiments revealed that the proposed method superiors conventional template-matching method by being capable of counting with significant improvement of speed as well as with higher accuracy and stronger robustness. We also considered the proposed method can be readily extended to data with similar properties.
Ittetsu Taniguchi received B.E., M.E., and Ph.D degrees from Osaka University in 2004, 2006, and 2009, respectively. From 2007 to 2008, he was an international scholar at Katholieke Universiteit Leuven (IMEC), Belgium. In 2009, he joined the College of Science and Engineering, Ritsumeikan University as an assistant professor, and became a lecturer in 2014. In 2017, he joined the Graduate School of Information Science and Technology, Osaka University as an associate professor. His research interests include system level design methodology, and combinatorial optimization problems. He is a member of IEEE, ACM, IEICE, IPSJ, and IEEJ.