| Speaker Name | Dr. Deepayan Bhowmik and Dr. Arijit Sur |
| Title | Watermarking Techniques for Scalable Coded Image and Video Authentication |
Biography
Dr. Deepayan Bhowmik is a research associate in the Vision Lab within the Institute of Sensors and Systems at Heriot-Watt University, Edinburgh. He received the B.E. in Electronics Engineering from Visvesvaraya National Institute of Technology (VNIT), Nagpur, India, the M.Sc. in Electronic and Information Technology from Sheffield Hallam University, UK and PhD from The University of Sheffield, UK. Deepayan received prestigious EPSRC/British Petroleum Dorothy Hodgkin Post Graduate Award (DHPA) for his PhD Study. Previously, he worked as research associate at The University of Sheffield, UK and as a system engineer in ABB Ltd., India. He has authored more than 20 peer reviewed research papers which have appeared in ACM MMSEC, IEEE-ISCAS, Springer IWDW, SPIE Electronic Imaging, and IET-IPR etc. His current research interests include programmable embedded image processor architecture, vision based crowd behaviour understanding, person tracking, image and video forensics etc.
Biography
Dr. Arijit Sur is an assistant professor in Computer Science Department at Indian Institute of Technology, Guwahati, India. He received his Ph.D. degree in Computer Science and Engineering from Indian Institute of Technology Kharagpur. He has received his M.Sc. in Computer and Information Science and M. Tech in Computer Science and Engineering, both from Department of Computer Science and Engineering, University of Calcutta. Dr. Sur received Institute Scholarship (IIT Kharagpur) and Infosys Scholarship for his PhD study. He also got Microsoft Outstanding Young Faculty Programme Award at Dept. of CSE, IIT Guwahati. He has published more than 25 peer reviewed international & national conference and journal papers and has been successful in securing number of project grants on multimedia security. His research interests include Multimedia Security e.g., Image and Video Watermarking, Reversible Data Hiding; Steganography & Steganalysis for Image and Video; and Scalable Video Streaming.
Abstract
Due to the increasing heterogeneity among the end user devices for playing multimedia content, scalable image and video communication attracts significant attention in recent days. Such advancements are duly supported by recent scalable coding standards for multimedia content coding, i.e., JPEG2000 for images, MPEG advanced video coding (AVC)/H.264 scalable video coding (SVC) extension for video, and MPEG-4 scalable profile for audio. In scalable coding, high-resolution content is encoded to the highest visual quality and the bit-streams are adapted to cater various communication channels, display devices, and usage requirements. However, protection and authentication of these contents are still challenging and not surprisingly attracts attention from researchers and industries. Digital watermarking, which has seen considerable growth in last two decades, is proposed in the literature as a solution for scalable content protection and authentication. Watermarking for scalable coded image and video, faces unique set of challenges with scalable content adaptation. The tutorial will share various research problems and solutions associated with the image and video watermarking techniques in this field. This tutorial will help the participants to understand 1) the image and video watermarking and its properties, 2) watermarking strategies for scalable coded image and video, and 3) lastly, the recent developments and the open questions in this field.
Outline
Digital watermarking (properties and applications) and frequency domain transforms used in watermarking, e.g., Discrete wavelet transform (DWT) (25 mins)
Scalable image and video coding and its application in multimedia signal processing (25 mins)
Research techniques for image watermarking for JPEG2000 content adaptation (40 mins)
Research techniques for video watermarking for content adaptation (50 mins)
Recent developments and open questions in this field (20 mins)