Keynote Speaker I
Fellow of IEEE and IAPR, Prof. David
Zhang, Hong Kong Polytechnic University, Hong Kong
David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in Computer Science from the Harbin Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. He is a Chair Professor since 2005 at the Hong Kong Polytechnic University where he is the Founding Director of the Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government in 1998. He also serves as Visiting Chair Professor in Tsinghua University, and Adjunct Professor in Peking University, Shanghai Jiao Tong University, HIT, and the University of Waterloo. He is Founder and Editor-in-Chief, International Journal of Image and Graphics (IJIG); Founder and and Series Editor, Springer International Series on Biometrics (KISB); Organizer, the 1st International Conference on Biometrics Authentication (ICBA); Associate Editor of more than ten international journals including IEEE Transactions and so on. So far, he has published over 10 monographs, 350 international journal papers and 35 patents from USA/Japan/HK/China. According to Google Scholar, his papers have got over30,000 citations and H-index is 81. He was selected as one of Thomson Reuters Highly Cited Researcher 2014. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.
Keynote Speaker II
Prof. Alexander Balinsky, Cardiff University, UK
Prof. Alexander Balinsky received his PhD degree in Mathematical Physics from the Landau Institute of Theoretical Physics in 1990 and was Research Fellow in the Department of Mathematics at The Technion-Israel Institute of Technology from 1993 till 1997. He joined Cardiff University in 1997.He is a Professor in the Cardiff School of Mathematics and WIMCS (Wales Institute of Mathematical and Computational Sciences) Chair in Mathematical Physics. His current research interests lie in the areas of spectral theory, stability of matter, image processing and machine learning. He has participated in EU TMR network on Partial Differential Equations and Quantum Mechanics (1996-2001).He was PI on three years grant from United State-Israel Binational Science Foundation (1996-1999),on three years EPSRC Research Grant 2003-2006.He was founding member of Cardiff Communication Research Center. In 2007-2011 he had joint with Hewlett-Packard EPSRC CASE award,and from October 2011 joint with Hewlett-Packard 50%-50% PhD Scholarship. He also did consultancy work for Reuters, London on athematical models for Internet Security.
Plenary Speaker I
Prof. Hsien-Chou Liao
Chaoyang University of Technology, Taiwan
Abstract: Pattern recognition or computer vision technology is very important to industrial automation or Industry 4.0. Several applications of pattern recognition technology in precision machinery and video surveillance industries are presented in this speech.
1. Embedded nighttime flame detection system
Intelligent video surveillance (IVS) is an important development direction. A flame detection technology was developed to detect flame at the nighttime. The process of the flame detection at the nighttime consists of three steps: bright area detection, motion detection, and blinking detection. Besides, eight sensitivities and three kinds of monitoring areas are designed. All the parameter settings for every sensitivity and monitoring area are also designed to increase the feasibility of the flame detection technology. The experiment results show that the detect time of nighttime is about 5~7 seconds.
2. Robust and precise image registration technology
Image registration technology is widely used in Precision Machining Industry (PMI). It is based on the correlation analysis of two images. Its objective is to avoid the error caused by human or machine during the operation of a machine. In this study, an image registration method is realized by using the correlation-based and feature-based methods. The comparison results between the proposed method and the popular Cognex library show that the average position delta is only 0.06~0.55 pixel and the average rotation delta is 0.03~0.05 degree in the normal cases.
3. High speed AOI defect detection system
Automatic or automated optical inspection, AOI, is key technique used in many manufacturing processes. This technology enables quick and accurate inspection for specific purposes to ensure that the final product achieves high quality standards and complies with the customer’s requirements. In this study, a high-speed metal can AOI system is developed. The manufacturing speed of metal cans is 800 cans/min. That is, the moving speed of a can is about 1.2 meters/sec and the inspection time is limited within 75ms. The width and height errors were only 0.14 mm and 0.09 mm, its shows that the proposed technique is accurate. The AOI system is also integrated with the PLC controller of the can manufacturing machine for rejecting defective can precisely under high speed condition.
Hsien-Chou Liao received the B.S. and Ph.D. degrees in Computer Science and Information Engineering from National ChiaoTung University in 1991 and 1998, respectively. He is a senior member of IEEE. He also managed many academic-industrial projects. He and his students received many awards of national or international competitions. His research interests include pattern recognition, computer vision, automated optical inspection, and location-based service.