Keynote Speakers

Prof. Chin-Chen Chang
IEEE and IET Fellows, Feng Chia University, Taiwan

Professor Chin-Chen Chang obtained his Ph.D. degree in computer engineering from National Chiao Tung University. His first degree is Bachelor of Science in Applied Mathematics and master degree is Master of Science in computer and decision sciences. Both were awarded in National Tsing Hua University. Dr. Chang served in National Chung Cheng University from 1989 to 2005. His current title is Chair Professor in Department of Information Engineering and Computer Science, Feng Chia University, from Feb. 2005. Prior to joining Feng Chia University, Professor Chang was an associate professor in Chiao Tung University, professor in National Chung Hsing University, chair professor in National Chung Cheng University. He had also been Visiting Researcher and Visiting Scientist to Tokyo University and Kyoto University, Japan. During his service in Chung Cheng, Professor Chang served as Chairman of the Institute of Computer Science and Information Engineering, Dean of College of Engineering, Provost and then Acting President of Chung Cheng University and Director of Advisory Office in Ministry of Education, Taiwan. Professor Chang's specialties include, but not limited to, data engineering, database systems, computer cryptography and information security. A researcher of acclaimed and distinguished services and contributions to his country and advancing human knowledge in the field of information science, Professor Chang has won many research awards and honorary positions by and in prestigious organizations both nationally and internationally. He is currently a Fellow of IEEE and a Fellow of IEE, UK. And since his early years of career development, he consecutively won Institute of Information & Computing Machinery Medal of Honor, Outstanding Youth Award of Taiwan, Outstanding Talent in Information Sciences of Taiwan, AceR Dragon Award of the Ten Most Outstanding Talents, Outstanding Scholar Award of Taiwan, Outstanding Engineering Professor Award of Taiwan, Chung-Shan Academic Publication Awards, Distinguished Research Awards of National Science Council of Taiwan, Outstanding Scholarly Contribution Award of the International Institute for Advanced Studies in Systems Research and Cybernetics, Top Fifteen Scholars in Systems and Software Engineering of the Journal of Systems and Software, Top Cited Paper Award of Pattern Recognition Letters, and so on. On numerous occasions, he was invited to serve as Visiting Professor, Chair Professor, Honorary Professor, Honorary Director, Honorary Chairman, Distinguished Alumnus, Distinguished Researcher, Research Fellow by universities and research institutes. He also published over serval hundred papers in Information Sciences. In the meantime, he participates actively in international academic organizations and performs advisory work to government agencies and academic organizations.

Speech Title: Applying De-clustering Concept to Information Hiding
Abstract: Reversible steganography allows an original image to be completely restored after the extraction of hidden data embedded in a cover image. In this talk, I will talk about a reversible scheme based on declustering strategy for VQ compressed images. The declustering can be regarded as a preprocessing step to make the proposed steganographic method more efficient. Our experimental results show that the time required for the embedding process in the proposed method is few. In addition, the reversible steganography allows an original image to be completely restored after the extraction of hidden data embedded in a cover image. In this talk,l will introduce a reversible scheme for VQ-compressed images that is based on a declustering strategy and takes advantage of the local spatial characteristics of the image. The main advantages of our method are ease of implementation, low computational demands,and no requirement for auxiliary data.


Prof. Ching-Nung Yang
IET Fellow, National Dong Hwa University, Taiwan

CHING-NUNG YANG received the B.S. degree and the M.S. degree, both from Department of Telecommunication Engineering at National Chiao Tung University. He received Ph.D. degree in Electrical Engineering from National Cheng Kung University. He is a professor in the Department of Computer Science and Information Engineering at National Dong Hwa University. Also, Prof. Yang is currently a Fellow of IET (IEE) and an IEEE senior member. He has published several hundreds of journal and conference papers in the areas of information security, multimedia security and coding theory. He is the guest editor of a special issue on "Visual Cryptography Scheme" for Communication of CCISA, and a coauthor of a series of articles on "Image Secret Sharing" for the Encyclopedia of Multimedia. He is the coeditor of two books "Visual Cryptography and Secret Image Sharing" published by CRC Press/Taylor & Francis, and "Steganography and Watermarking" published by Nova Science Publishers, Inc. He serves as a technical reviewer for over 30 major scientific journals in the areas of his expertise, and serves as editorial boards of some journals. Also, has served chairs, keynote speakers, and members of program committees of various international conferences. He is the recipient of the 2000, 2006, 2010, 2012, and 2014 Fine Advising Award in the Thesis of Master/PhD of Science awarded by Institute of Information & Computer Machinery. His current research interests include coding theory, information security, and cryptography.
Speech Title: Secure Image Secret Sharing over Distributed Cloud Network
Abstract: A well-known (k, n) secret image sharing (SIS) scheme is the threshold scheme to share a secret image into n shadow images, and the secret image can be recovered from any k shadow images. However, all previous SIS schemes do not deal with reconstructing secret image over distribute cloud network (DCN). To enable secure reconstruction over DCN, we need private communication channels among all involved participants holding shadow images. A naive implementation of secure communication is using an extra key distribution protocol to deliver a common key to all participants. This talk introduces a (k, n)-SIS over DCN, which still has the threshold property (recover the secret image from any k shadow images) and meanwhile provides secure reconstruction over DCN, i.e., this scheme may non-interactively share a common key among any k participants. .


Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France

Salah Bourennane is currently a full Professor and he held also the position of the Dean of Research at the Ecole Centrale de Marseille, France. He is also the head of the Multidimensional Signals Group at Institut Fresnel, Marseille. He has over 30 years of research experience in the field of signal and image processing. His current research interests include statistical signal processing, array processing, image processing, remote sensing, tensor signal processing, and performance analysis. He authored over 350 research papers in various top-tier international journals and conferences, and edited many books and served as a guest editor of several special issues. He served on the editorial boards of many international journals and proceedings including the International Journal of Signal Processing, Image Processing and Pattern Recognition, The International Journal of Image and Signal Systems Engineering, Journal of Remote Sensing and Technology, among others. He has served on the technical program committees for numerous premier conferences and workshops including Advanced Concepts for Intelligent Vision Systems, International conference on latent variable analysis and signal separation, International Conference on Vision, Image and Signal Processing, and many others. He was an organizer of several international conferences such as the 6th European Workshop on Visual Information Processing at Marseille, 2016. He received a Ph.D. degree from Institut National Polytechnique de Grenoble, France, in signal processing..

Title: Tensorial Signal Processing: Image Denoising with Rare Signal Preserving

Abstract: A hyperspectral image is a multidimensional array also named as a tensor and it normally consists of hundreds of spectral bands. So, HSI data, for instance,airborne hyperspectral images HYDICE (Hyperspectral Digital Imagery Collection Experiment), has two spatial dimensions and one spectral dimension. While acquired images in hyperspectral imagery are disturbed by additive noise, which can degrade classifcation and target detection results. To reduce the noise, HSI is commonly split into vectors or matrix so any 2D filtering method could be applied, but this splitting way does not consider the related information between image planes. So, some new approaches, such as tensor decomposition methods, have been used to denoise those images and showed some prospects in this field. There are two main decomposition models for multidimensional arrays: TUCKER3 (Three-mode factor analysis) decomposition and PARAFAC/CANDECOMP (Canonical Decomposition / Parallel Factor Analysis) decomposition.