Hands-On Image Processing with Python

Explore the world of image processing and CV (computer vision) with Python from fundamental concepts to deep learning

Key Features

Get to grips with image enhancement, restoration, segmentation, feature-extraction, classification, object detection, and image synthesis
Benefit from hands-on guidance for vital image processing tasks using Python libraries
Familiarize yourself with various techniques, spanning classical, machine learning, and cutting-edge deep learning methods
Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionBeing able to process, extract information, and understand an image quickly has become a critical part of real-world applications within security, payment, healthcare, advertising, and other sectors. This book covers a wide range of topics, following a highly practical approach that takes you through a set of image processing concepts and algorithms to help you learn how to use leading Python library functions to implement these algorithms.

As you progress, you’ll gain proficiency in writing code snippets in Python 3 and quickly implement complex image processing and computer vision algorithms to solve problems in image enhancement, restoration, denoising, segmentation, classification, object detection and more, using image processing libraries such as PIL, scikit-mage, scipy ndimage, and opencv-python. You’ll also learn how to use ML models using scikit-learn and explore recent advances with deep learning models with CNNs (e.g., ResNet, Yolo) using tensorflow, keras, and pytorch. The final set of chapters will help you solve advanced problems, such as image-to-image translation, anisotropic diffusion, and generative arts.

By the end of this book, you will be well versed in image processing and ready to solve a variety of commonly occurring problems. What you will learn

Gain expertise in tackling digital image processing problems from diverse perspectives
Explore the intricacies of image transformation, enhancement, spatial and frequency domain filters, and morphological image processing
Dive into the realm of image restoration and inpainting
Harness the power of ML models for image classification and object detection
Embark on a journey into the realm of deep learning, including CNNs, attention mechanisms, autoencoders, GANs, and transfer learning
Push the boundaries with image captioning, pseudo coloring, 3D image processing, generative art, and quantum image processing
Apply your knowledge to real-world domains, including medical imaging, security systems, and remote sensing applications

Who this book is forThis book is for engineers and applied researchers interested in CV, image processing, ML and deep learning, especially those who are proficient in Python programming and want to learn how to implement different algorithms for image processing. Working knowledge of Python is a must.