VLSI is a well-established field of research that ignited the modern computing revolution. Serving as a guide to future developments, this book provides the frame of design, modeling concepts, and application of Image Processing based systems using VLSI design techniques. This volume focuses on biomedical applications where image processing-based hardware design is used for applications such as cancer detection, ECG, EEG measurements, medical imaging-based healthcare systems, and smart homes for elderly and disabled people. The book will help the research community to get in-depth knowledge of various systems that can be designed with image processing techniques using hardware.
Key Features:
- Describes concepts of state-of-the-art Image processing-based VLSI Design.
- Describes the Hardware implementation of image and video processing algorithms.
- Offers real-time hardware system design for smart cities.
- Develops dedicated hardware design for medical image processing applications.
- Explores VLSI design for Cognitive Science, Augmented Reality and Virtual Reality.
Table of Contents:
Preface 1 Biomedical image signal processing and its VLSI implementation–past, present and future 2 Methodology for real-time processing of medical images, based on GPU architecture 3 Genesis of abdominal electrode placements to create a non-invasive FECG database for scientific research 4 Unsupervised convolutional neural network model for breast cancer detection 5 Sign language recognition (SLR) system for hearing-impaired people and those with speech disability: a review 6 Image recognition with speech 7 Methodology for the creation and evaluation of a database of medical images: cerebral cysticercosis case 8 Smart homes: the next urban evolution in smart cities for elderly and disabled people to give a better quality of life 9 Practical techniques for the fight against COVID-19: using today’s technology to make prevention strategy more efficient and effective 10 Field programmable gate array implementation of MRI image segmentation for brain tumor detection and classification using a deep learning algorithm 11 A review on secure image transfer techniques and hardware security 12 Design and development of an iOS mobile application with the help of VLSI design 13 High level synthesis of fingerprint authentication system 14 An efficient 24×7 patient’s vital parameter monitoring framework using machine learning based Internet of Biomedical Things: a comprehensive approach 15 FPGA implementation for machine learning based automatic facial emotion recognition system 16 Role of reduction techniques in VLSI design
About the Author :
Dr. Sandeep Saini has
been active in field of VLSI design and hardware implementation for more than a
decade. He has published more than 30 articles in reputed Journals and
conferences. He has guided 10 PG thesis in the field of VLSI design, hardware
implementation, image processing-based hardware and reversible logic design.
Dr. Kusum Lata is an Associate Professor in the Department of Electronics and Communication Engineering at LNMIIT-Jaipur. She received M.Tech. and Ph.D. degrees from the Indian Institute of Technology (IIT), Roorkee, India and Indian Institute of Science (IISc), Bangalore, India. She has authored or co-authored more than 30 technical papers and 1 book chapter. Her research interests include digital circuit design using FPGAs, Design for Testability, Formal Verification of Analog and Mixed Signal Designs and Hardware Security.
Dr. Abhishek Sharma received his PhD in Engineering from University of Genoa, Italy. He is presently working as an Assistant professor in the Department of Electronics and Communication Engineering at The LNM Institute of Information and Technology, Jaipur, India. He is the centre lead of the LNM-Center of Smart Technology, and has filed 5 patents.
Dr. G R Sinha has made significant advancements in the fields of academic research and consultancy. He is known globally as an expert in the emerging topic of VLSI design.
