Download Free Hybrid Image And Signal Processing Book in PDF and EPUB Free Download. You can read online Hybrid Image And Signal Processing and write the review.

In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book: Provides broad background on various image thresholding and segmentation techniques Discusses information on various assessment metrics and the confusion matrix Proposes integration of the thresholding technique with the bio-inspired algorithms Explores case studies including MRI, CT, dermoscopy, and ultrasound images Includes separate chapters on machine learning and deep learning for medical image processing
This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
The first book to offer practical applications of neural networks to solve problems in digital signal processing and imaging. A highly practical book with a minimum of math and a wealth of examples. Disk includes a complete program for training, testing, and using neural networks along with C++ subroutines for all techniques discussed and source for the book's example code.
Digital Signal Processing System Design combines textual and graphical programming to form a hybrid programming approach, enabling a more effective means of building and analyzing DSP systems. The hybrid programming approach allows the use of previously developed textual programming solutions to be integrated into LabVIEW's highly interactive and visual environment, providing an easier and quicker method for building DSP systems. This book is an ideal introduction for engineers and students seeking to develop DSP systems in quick time. Features: - The only DSP laboratory book that combines textual and graphical programming - 12 lab experiments that incorporate C/MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature - Lab experiments covering basic DSP implementation topics including sampling, digital filtering, fixed-point data representation, frequency domain processing - Interesting applications using the hybrid programming approach, such as a software-defined radio system, a 4-QAM Modem, and a cochlear implant simulator - The only DSP project book that combines textual and graphical programming - 12 Lab projects that incorporate MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature - Interesting applications such as the design of a cochlear implant simulator and a software-defined radio system
This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.