Python Image Processing Cookbook
- Paperback: 438 pages
- Publisher: WOW! eBook (April 17, 2020)
- Language: English
- ISBN-10: 1789537142
- ISBN-13: 978-1789537147
Python Image Processing Cookbook: Explore Keras, scikit-image, OpenCV, Matplotlib, and many 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.
- Implement supervised and unsupervised machine learning algorithms for image processing
- Use deep neural network models for advanced image processing tasks
- Perform 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 in images using Tesseract, the optical character recognition (OCR) engine
- Understand image enhancement techniques such as gradient blending
By the end of this Python Image Processing Cookbook book, you’ll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.