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Image Processing Masterclass With Python


Image Processing Masterclass With Python
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Image Processing Masterclass With Python


Image Processing Masterclass With Python
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Author : Sandipan Dey
language : en
Publisher: BPB Publications
Release Date : 2021-03-10

Image Processing Masterclass With Python written by Sandipan Dey and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Computers categories.


Over 50 problems solved with classical algorithms + ML / DL models KEY FEATURESÊ _ Problem-driven approach to practice image processing.Ê _ Practical usage of popular Python libraries: Numpy, Scipy, scikit-image, PIL and SimpleITK. _ End-to-end demonstration of popular facial image processing challenges using MTCNN and MicrosoftÕs Cognitive Vision APIs. Ê DESCRIPTIONÊ 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.Ê 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 problems using differentÊ algorithms such as spatial filters and create a super resolution image using SRGAN. Finally, it explores popular facial image processing problems and solves them with Machine learning and Deep learning models using popular python ML / DL libraries. WHAT YOU WILL LEARNÊÊ _ Develop strong grip on the fundamentals of Image Processing and Image Manipulation. _ Solve popular Image Processing problems using Machine Learning and Deep Learning models. _ Working knowledge on Python libraries including numpy, scipyÊ and scikit-image. _ Use popular Python Machine Learning packages such as scikit-learn, Keras and pytorch. _ Live implementation of Facial Image Processing techniques such as Face Detection / Recognition / Parsing dlib and MTCNN. WHO THIS BOOK IS FORÊÊÊ This book is designed specially for computer vision users, machine learning engineers, image processing experts who are looking for solving modern image processing/computer vision challenges. TABLE OF CONTENTS 1. Chapter 1: Basic Image & Video Processing 2. Chapter 2: More Image Transformation and Manipulation 3. Chapter 3: Sampling, Convolution and Discrete Fourier Transform 4. Chapter 4: Discrete Cosine / Wavelet Transform and Deconvolution 5. Chapter 5: Image Enhancement 6. Chapter 6: More Image Enhancement 7. Chapter 7: Facel Image Processing



Image Processing And Computer Vision Masterclass With Python


Image Processing And Computer Vision Masterclass With Python
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Author : Sandipan Dey
language : en
Publisher: BPB Publications
Release Date : 2025-07-31

Image Processing And Computer Vision Masterclass With Python written by Sandipan Dey and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-31 with Computers categories.


DESCRIPTION Image processing and computer vision technologies, combined with the rapid advancements in generative AI, have become foundational to many modern applications. As visual data continues to grow exponentially, the ability to analyze, interpret, and generate images using advanced algorithms and AI is more critical than ever for driving innovation across industries. This book provides a thorough exploration of advanced techniques and practical implementations in the field of computer vision. This book offers a problem-oriented approach that bridges traditional image processing with modern machine learning and generative AI methods. ​​This new edition significantly expands into specialized domains with medical imaging applications using professional libraries like pydicom, ITK, and nnUNet for clinical diagnosis, including COVID-19 detection and brain tumor segmentation, plus remote sensing analysis with satellite processing. By the end of this book, readers will have developed strong practical skills in both classical and cutting-edge image processing and computer vision techniques, empowered to confidently design, implement, and adapt solutions across a wide range of real-world applications. They will emerge with a deep understanding of theory, hands-on coding experience, and the ability to leverage AI and generative models to push the boundaries of visual computing. WHAT YOU WILL LEARN ● Restore and enhance images using classical and deep learning methods. ● Segment images with advanced clustering and neural network techniques. ● Extract and match features for image alignment and recognition. ● Build and train image classifiers with ML and AI. ● Learn advanced restoration and inpainting techniques using cutting-edge deep learning models. ● Explore specialized domain expertise in medical imaging applications using professional libraries. WHO THIS BOOK IS FOR This book is ideal for undergraduate and graduate students, researchers, and professionals in computer vision, image processing, and AI. It also serves computer vision engineers, image analysts, data scientists, software engineers, and industry practitioners seeking practical, hands-on expertise using Python. TABLE OF CONTENTS 1. Image Restoration and Inverse Problems in Image Processing 2. More Image Restoration and Image Inpainting 3. Image Segmentation 4. More Image Segmentation 5. Image Feature Extraction and Its Applications: Image Registration 6. Applications of Image Feature Extraction 7. Image Classification 8. Object Detection and Recognition 9. Application of Image Processing and Computer Vision in Medical Imaging 10. Application of Image Processing and Computer Vision in Medical Imaging and Remote Sensing 11. Miscellaneous Problems in Image Processing and Computer Vision



Learn Python Programming Masterclass


Learn Python Programming Masterclass
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Author : Sure Academy
language : en
Publisher: Sure Academy
Release Date : 2025-01-08

Learn Python Programming Masterclass written by Sure Academy and has been published by Sure Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-08 with Computers categories.


Whether you want to: - build the skills you need to get your first Python programming job - move to a more senior software developer position - get started with Machine Learning, Data Science, Django or other hot areas that Python specialises in - or just learn Python to be able to create your own Python apps quickly. This book is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python. The fact is, Python is one of the most popular programming languages in the world



Python Image Processing Cookbook


Python Image Processing Cookbook
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Author : Sandipan Dey
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-17

Python Image Processing Cookbook written by Sandipan Dey and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-17 with Computers categories.


Explore Keras, scikit-image, open source computer vision (OpenCV), Matplotlib, and a wide range of other Python tools and frameworks to solve real-world image processing problems Key FeaturesDiscover solutions to complex image processing tasks using Python tools such as scikit-image and KerasLearn popular concepts such as machine learning, deep learning, and neural networks for image processingExplore common and not-so-common challenges faced in image processingBook Description With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing. With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems. By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively. What you will learnImplement supervised and unsupervised machine learning algorithms for image processingUse deep neural network models for advanced image processing tasksPerform image classification, object detection, and face recognitionApply image segmentation and registration techniques on medical images to assist doctorsUse classical image processing and deep learning methods for image restorationImplement text detection in images using Tesseract, the optical character recognition (OCR) engineUnderstand image enhancement techniques such as gradient blendingWho this book is for This book is for image processing engineers, computer vision engineers, software developers, machine learning engineers, or anyone who wants to become well-versed with image processing techniques and methods using a recipe-based approach. Although no image processing knowledge is expected, prior Python coding experience is necessary to understand key concepts covered in the book.



Image Processing And Acquisition Using Python


Image Processing And Acquisition Using Python
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Author : Ravishankar Chityala
language : en
Publisher: CRC Press
Release Date : 2020

Image Processing And Acquisition Using Python written by Ravishankar Chityala and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Image processing categories.


Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing--one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry. Features Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images. Contains many examples, detailed derivations, and working Python examples of the techniques. Offers practical tips on image acquisition and processing. Includes numerous exercises to test the reader's skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book's web page. New to this edition Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks. A new chapter on affine transform and many new algorithms. Updated Python code aligned to the latest version of modules.



Hands On Image Processing With Python


Hands On Image Processing With Python
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Author : Sandipan Dey
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30

Hands On Image Processing With Python written by Sandipan Dey and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.


Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.



Python 3 Image Processing


Python 3 Image Processing
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Author : Pajankar Ashwin
language : en
Publisher: BPB Publications
Release Date : 2019-09-20

Python 3 Image Processing written by Pajankar Ashwin and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.


Gain a working knowledge of practical image processing and with scikit-image.Key features Comprehensive coverage of various aspects of scientific Python and concepts in image processing. Covers various additional topics such as Raspberry Pi, conda package manager, and Anaconda distribution of Python. Simple language, crystal clear approach, and straight forward comprehensible presentation of concepts followed by code examples and output screenshots. Adopting user-friendly style for explanation of code examples.DescriptionThe book has been written in such a way that the concepts are explained in detail, giving adequate emphasis on code examples. To make the topics more comprehensive, screenshots and code samples are furnished extensively throughout the book. The book is conceptualized and written in such a way that the beginner readers will find it very easy to understand the concepts and implement the programs.The book also features the most current version of Raspberry Pi and associated software with it. This book teaches novice beginners how to write interesting image processing programs with scientific Python ecosystem. The book will also be helpful to experienced professionals to make transition to rewarding careers in scientific Python and computer vision. What will you learn Raspberry Pi, Python 3 Basics Scientific Python Ecosystem NumPy and Matplotlib Visualization with Matplotlib Basic NumPy, Advanced Image Processing with NumPy and Matplotlib Getting started with scikit-image Thresholding, Histogram Equalization, and Transformations Kernels, Convolution, and Filters Morphological Operations and Image Restoration Noise Removal and Edge Detection Advanced Image Processing OperationsWho this book is for Students pursuing BE/BSc/ME/MSc/BTech/MTech in Computer Science, Electronics, Electrical, and Mathematics Python enthusiasts Computer Vision and Image Processing professionals Anyone fond of tinkering with Raspberry Pi Researchers in Computer Vision Table of contents1. Concepts in Image Processing2. Installing Python 3 on Windows3. Introduction to Raspberry Pi4. Python 3 Basics5. Introduction to the Scientific Python Ecosystem6. Introduction to NumPy and Matplotlib7. Visualization with Matplotlib8. Basic Image Processing with NumPy and Matplotlib9. Advanced Image Processing with NumPy and Matplotlib10. Getting Started with Scikit-Image11. Thresholding Histogram Equalization and Transformations12. Kernels, Convolution and Filters13. Morphological Operations and Image Restoration14. Noise Removal and Edge Detection15. Advanced Image Processing Operations16. Wrapping UpAbout the authorAshwin Pajankar is a polymath. He has more than two decades of programming experience. He is a Science Popularizer, a Programmer, a Maker, an Author, and a Youtuber. He is passionate about STEM (Science-Technology-Education-Mathematics) education. He is also a freelance software developer and technology trainer. He graduated from IIIT Hyderabad with M.Tech. in Computer Science and Engineering. He has worked in a few multinational corporations including Cisco Systems and Cognizant for more than a decade. Ashwin is also an online trainer with various eLearning platforms like BPBOnline, Udemy, and Skillshare. In his free time, he consults on the topics of Python programming and data science to the local software companies in the city of Nasik. He is actively involved in various social initiatives and has won many accolades during his student life and at his past workplaces.His Website: http://www.ashwinpajankar.com/His LinkedIn Profile: https://www.linkedin.com/in/ashwinpajankar/



Practical Machine Learning And Image Processing


Practical Machine Learning And Image Processing
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Author : Himanshu Singh
language : en
Publisher: Apress
Release Date : 2019-02-26

Practical Machine Learning And Image Processing written by Himanshu Singh and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-26 with Computers categories.


Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the conceptsin Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will Learn Discover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.



Subject Guide To Forthcoming Books


Subject Guide To Forthcoming Books
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Author :
language : en
Publisher:
Release Date : 1983

Subject Guide To Forthcoming Books written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with American literature categories.


Presents by subject the same titles that are listed by author and title in Forthcoming books.



Digital Image Processing


Digital Image Processing
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Author : S Esakkirajan
language : en
Publisher: Springer
Release Date : 2025-07-04

Digital Image Processing written by S Esakkirajan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Computers categories.


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 with illustrative examples in Python. Each chapter begins with clear learning objectives and concludes with exercises and multiple-choice questions for self-assessment. Drawing from a diverse range of sources including research articles and books, the references provided at the end of each chapter encourage further exploration. Tailored for undergraduate and postgraduate students, research scholars, engineers, and faculty specializing in image processing, it assumes a foundational understanding of set theory, matrix algebra, probability, and random variables.