Haar-like features are very useful image features used in object detection. They were introduced in the very first real-time face detector by Viola and Jones. Using integral images, Haar-like features of any size (scale) can be efficiently computed in constant time. The computation speed is the key advantage of a Haar-like feature over most other features. Using the Viola-Jones face detection algorithm, faces can be detected in an image using these Haar-like features. Each Haar-like feature acts as just a weak classifier, and hence a huge number of these features are required to detect a face with good accuracy. Therefore, a large number of features are computed for all possible locations and sizes of each Haar-like kernel, using the integral images. Then, an AdaBoost ensemble classifier is used to select important features from...
Python Image Processing Cookbook
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Python Image Processing Cookbook
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Overview of this book
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.
Table of Contents (11 chapters)
Preface
Image Manipulation and Transformation
Free Chapter
Image Enhancement
Image Restoration
Binary Image Processing
Image Registration
Image Segmentation
Image Classification
Object Detection in Images
Face Recognition, Image Captioning, and More
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