English | 2020 | ISBN: 978-1789537147 | 435 Pages | PDF, EPUB | 1229 MB
Explore Keras, scikit-image, OpenCV, Matplotlib, and many other Python tools and frameworks to solve real-world image processing problems
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
Resolve the captcha to access the links!