Proceedings of 3rd International Conference on Computer Vision and Image Processing: Cvip 2018, Volume 1

ISBN-13: 9789813290877 / Angielski / Miękka / 2019 / 472 str.

Bidyut B. Chaudhuri; Masaki Nakagawa; Pritee Khanna

O autorze

Bidyut Baran Chaudhuri is currently Pro Vice Chancellor of Techno India University, Salt Lake, Calcutta, India. Previously he was INAE Distinguished Professor at Indian Statistical Institute, Calcutta. He received his B.Sc. (Hons), B.Tech, and M.Tech. degrees from Calcutta University, India, and his Ph.D. from the Indian Institute of Technology Kanpur, in 1980. He did his postdoc work as Leverhulme fellow at Queen’s University, UK and acted as a visiting faculty at the Technical University, Hannover, Germany. His main research interests are in Pattern Recognition, Image Processing, Language processing and Machine learning in which he has published 450 research Papers and five books. He is a life fellow of IEEE, IAPR, TWAS as well as fellow of Indian Academies like INAE, INSA, INASc. He has received many awards for his research work. Prof. Chaudhuri is now an Associate Editor of the International Journal of Document Analysis and Recognition (IJDAR), International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI). In the past he worked in such capacity in several other international journals.  

Masaki Nakagawa is a Professor of Media Interaction at the Department of Computer and Information Sciences, Tokyo University of Agriculture and Technology, Japan. He graduated from the University of Tokyo in March 1977 and pursued an M.Sc. course in Computer Studies at Essex University, England, sponsored by the Japanese Government. In March 1979, he graduated from the University of Tokyo with an M.Sc. in Physics. In July 1979, he completed his M.Sc. in Computer Studies at Essex University in England, and in December 1988, he completed his Ph.D. at the University of Tokyo. His work chiefly focuses on handwriting recognition and pen-based user interfaces and applications, especially educational applications. Prof. Nakagawa has over 300 publications to his credit.

Pritee Khanna is an Associate Professor and Head of the Computer Science & Engineering Discipline, PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur. Her main areas of interest include Biometrics, Biomedical Image Processing, Image Retrieval and Indexing, Dynamic Gesture Recognition, and Computer -Aided Product Design. She is a recipient of UGC Fellowship, India and Long Term JSPS Fellowship, Japan.  She is a senior member of the IEEE Computer Society and a life member of IAENG. She has published 89 papers in journals and conference proceedings.

Sanjeev Kumar is an Associate Professor of Mathematics at the IIT Roorkee, India. His areas of interest include Computer Vision & Mathematical Imaging, Inverse Problems, and Machine Learning. He completed his Ph.D. in Mathematics at the IIT Roorkee in 2008. He is a member of the IEEE Computer Society and International Association of Pattern Recognition, and a life member of the ACEEE and IACSIT. He has published over 40 papers in journals and conference proceedings.

Blurb

This book is a collection of carefully selected works presented at the Third International Conference on Computer Vision & Image Processing (CVIP 2018). The conference was organized by the Department of Computer Science and Engineering of PDPM Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India during September 29–October 01, 2018. All the papers have been rigorously reviewed by the experts from the domain. This 2 volume proceedings include technical contributions in the areas of Image/Video Processing and Analysis; Image/Video Formation and Display; Image/Video Filtering, Restoration, Enhancement and Super-resolution; Image/Video Coding and Transmission; Image/Video Storage, Retrieval and Authentication; Image/Video Quality; Transform-based and Multi-resolution Image/Video Analysis; Biological and Perceptual Models for Image/Video Processing; Machine Learning in Image/Video Analysis; Probability and uncertainty handling for Image/Video Processing; and Motion and Tracking.