Python Image Processing Cookbook
- Length: 435 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2021-01-11
- ISBN-10: 1789537142
- ISBN-13: 9781789537147
- Sales Rank: #2317330 (See Top 100 Books)
Explore Keras, scikit-image, OpenCV, Matplotlib, and many other Python tools and frameworks to solve real-world image processing problems
Key Features
- Discover solutions to complex image processing tasks using Python tools such as scikit-image and Keras
- Delve into popular concepts such as machine learning, deep learning, and neural networks for image processing
- Explore common and not-so-common challenges faced in image processing
Book Description
With advancements in wireless devices and mobile technology, there’s an ever-increasing demand for digital image processing skills to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of tools, algorithms, 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 image detection, image segmentation, and image reconstruction using large hybrid data sets. This book will also guide you in 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 to apply deep learning-based techniques such as transfer learning and fine-tuning to solve real-world problems.
By the end of this book, you’ll be equipped with the skills you need to apply image processing techniques effectively to leverage the complete capabilities of the Python ecosystem.
What you will learn
- Implement supervised and unsupervised machine learning algorithms for image processing
- Use deep neural network models for advanced image processing tasks
- Perform key tasks like image classification, object detection, and face recognition
- Apply image segmentation and registration techniques on medical images to assist doctors
- Use classical image processing and deep learning methods for image restoration
- Implement text detection from images to use with optical character recognition (OCR)
- Get to grips with image enhancement techniques
Who This Book Is For
This book is for image processing engineers, computer vision engineers, software developers, machine learning engineers, and anyone who wants to become well-versed with image processing techniques and methods using a recipe-based approach. Though no image processing knowledge is expected, prior Python coding experience is necessary to understand key concepts covered in the book.
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