Intelligent Multimedia Processing and Computer Vision: Techniques and applications

by Shyam Singh Rajput (Editor), Chen Chen (Editor), Karm Veer Arya (Editor)

Overview

Intelligent multimedia involves the computer processing and understanding of perceptual input from speech, text, videos and images. Reacting to these inputs is complex and involves research from engineering, computer science and cognitive science. Intelligent multimedia processing deals with the analysis of images and videos to extract useful information for numerous applications including medical imaging, robotics, remote sensing, autonomous driving, AR/VR, law enforcement, biometrics, multimedia enhancement and reconstruction, agriculture, and security. Intelligent multimedia processing and computer vision have seen an upsurge over the last few years. With the increasing use of intelligent multimedia processing techniques in various sectors, the requirement for fast and reliable techniques to analyse and process multimedia content is increasing day by day.

Intelligent Multimedia Processing and Computer Vision: Techniques and applications reviews cutting edge research in the areas of intelligent multimedia processing and computer vision techniques and applications with a particular emphasis on interdisciplinary approaches and novel solutions. The book is aimed at practicing engineers, scientists, technology professionals, researchers and advanced students in the fields of multimedia processing and security, image processing, computer vision, biometrics, intelligent and smart technologies, machine learning and deep learning, and autonomous systems.

Product Details

ISBN-13:	9781839537257
Publisher:	The Institution of Engineering and Technology
Publication date:	12/05/2023
Series:	Computing and Networks
Pages:	369
Product dimensions:	6.14(w) x 9.21(h) x (d)

About the Author

Shyam Singh Rajput is an assistant professor at the Department of Computer Science & Engineering (CSE), National Institute of Technology Patna, India. His research interests include image processing, computer vision, ad-hoc networks, and information security. He has published over 45 journal and conference papers in the areas of image processing, computer vision, wireless ad-hoc networks, and information security. He holds an Indian Patent and has edited a book on Digital Image Enhancement and Reconstruction. He is a member of the IEEE and the ACM. He earned his PhD degree in CSE from the ABV-Indian Institute of Information Technology and Management, Gwalior, India.

Chen Chen is an assistant professor at the Center for Research in Computer Vision (CRCV), University of Central Florida, USA. His main research interests include computer vision, image and video processing and machine learning. He is an associate editor for the IEEE Journal on Miniaturization for Air and Space Systems, Journal of Real-Time Image Processing, Signal, Image and Video Processing, and Sensors Journal. He is a member of the SIAM, IEEE, ACM, and IET. He holds a PhD degree in electrical engineering from the University of Texas at Dallas, USA.

Karm Veer Arya is a professor at the ABV-Indian Institute of Information Technology & Management (IIITM), Gwalior, India. He has published several books including Security in Mobile Ad-hoc Networks, Emerging Wireless Communication and Biometric Computing, as well as book chapters and over 200 journal and conference papers in the areas of image processing, biometrics, and information security. He is on the editorial board of international journals and is a member of organizing committees and programs committee for conferences and workshops. He is a senior member of the IEEE, fellow of the IETE, fellow of the IE and life member of the ISTE. He holds a PhD degree in Computer Science and Engineering from the Indian Institute of Technology Kanpur, India.

Table of Contents

• Chapter 1: Introduction
• Chapter 2: State-of-the-art analysis of deep learning techniques for image segmentation
• Chapter 3: Biometric-based computer vision for boundless possibilities: process, techniques, and challenges
• Chapter 4: Channel refinement of fingerprint pre-processing models
• Chapter 5: A review of deep learning approaches for video-based crowd anomaly detection
• Chapter 6: Natural language and mathematical reasoning
• Chapter 7: AI and machine learning in medical data processing
• Chapter 8: Progress of deep learning in digital pathology detection of chest radiographs
• Chapter 9: Computer vision and modern machine learning techniques for autonomous driving
• Chapter 10: Dehazing and vision enhancement: challenges and future scope
• Chapter 11: Machine learning and revolution in agriculture: past, present and future
• Chapter 12: AI- and ML-based multimedia processing for surveillance
• Chapter 13: Action recognition techniques
• Chapter 14: Conclusion