Showing results for "Principles of digital image processing English"

Integrate machine learning and AI-based approaches into practical image processing with PythonEngineers and researchers implementing image processing systems need methods that bridge classical techniques with modern machine learning approaches. This book delivers both traditional and modern AI-based methods and algorithms in image enhancement, restoration, segmentation, compression, and analysis. Written by an educator and researcher with more than 40 years’ experi...

"Fundamentals of Digital Image Processing" is a comprehensive guide that delves into the intricacies of manipulating and analyzing digital images. We provide a thorough exploration of fundamental concepts, techniques, and applications in digital image processing. Catering to both beginners and seasoned professionals, the content spans a wide spectrum.Starting with the basics, we introduce core principles of digital image representation, pixel operations, and color models. We then pr...

This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applications—ideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like deep learning fundamentals, deepfake technology, adversarial attacks in computer vision, adaptive cryptography, and generative AI-driven SAR-to-optical image translation. As a post...

Is there any reason to believe the opposite of my current belief? Is scope creep really all bad news? What will be the consequences to the stakeholder (financial, reputation etc) if Digital image processing does not go ahead or fails to deliver the objectives? How will you motivate the stakeholders with the least vested interest? What tools and technologies are needed for a custom Digital image processing project?Defining, designing, creating, and implementing a process to solve a ...

This unique reference presents in-depth coverage of the latest methods and applications of digital image processing describing various computer architectures ideal for satisfying specific image processing demands.

The subject of digital image processing has migrated from a graduate to a junior or senior level course as students become more proficient in mathematical background earlier in their college education. With that in mind, Introduction to Digital Image Processing is simpler in terms of mathematical derivations and eliminates derivations of advanced s

In this book we will cover a range of topics related to DIP, these topics include:- Introduction to digital images.- Images types.- Image arithmetic.- Image enhancement and filtering.- Edge detection.- Image morphology and applications.- Image features extraction methods.- Selecting a feature extraction method to build features data base.- Introduction to Artificial neural networks (ANN).- Building image recognition syst...

This book starts with basic Image Processing and manipulation problems and demonstrates how to solve them with popular Python libraries and modules. It then concentrates on problems based on Geometric image transformations and problems to be solved with Image hashing.Next, the book focuses on solving problems based on Sampling, Convolution, Discrete Fourier transform, Frequency domain filtering and image restoration with deconvolution. It also aims at solving Image enhancement problemsusin...

This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging.There is a need to be able to understand and analyse the latest developments o...

The book provides a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives are to offer an overview to the elementary concepts and practices appropriate to digital image processing as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to:Applications and tool...

Highly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial SoftwareA Computational Introduction to Digital Image Processing, Second Edition explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that

Digital image processing plays a crucial role in facilitating efficient storage, transmission, manipulation, and retrieval of images. Python, renowned for its open-source nature and strong community support, offers a user-friendly platform with extensive image processing capabilities through libraries such as computer vision and scikit-learn.This textbook serves as a practical guide to digital image processing using Python, presenting fundamental concepts, techniques, and algorithms...