Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

by Sandipan Dey

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 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. 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.

ebook

Published April 17, 2020

Reviews

[Johnny · Rating 1 out of 5]

The first thing you notice with this book is the bad image quality. That is a bad start for a book about image processing. On too many examples you have to ask yourself is this artefact on the image there by design or by accident.

If we look a bit deeper, more problems emerge. Sometimes there is no before image and only an after image, or vice-versa. That makes it hard to follow and understand the effect the author covers in this part of the book. In other parts we get a lot of new terms but no explanations for any of them. Algorithms get introduced, but not explained and we end up with various approaches to solve the same problem. Which one to use in which situation is up to the reader to figure out.

I understand the purpose of a cookbook and that it should follow the problem-solution pattern. Yet this book offers so many solutions to the same problem using so many different libraries that we end up with a mess.