Thresholding refers to a family of algorithms that use a pixel value as a threshold to create a binary image (an image with only black-and-white pixels) from a grayscale image (this is the simplest possible method, segmenting foreground objects from the background in an image). The threshold can be chosen manually (by looking at the histogram of pixel values) or automatically using an algorithm. Image segmentation techniques may be noncontextual (without considering spatial relationships between the features in an image and grouping pixels only with regard to certain global attributes—for example, color/gray level) or contextual (additionally exploiting spatial relationships). In this recipe, you will learn how to use a couple of popular histogram-based thresholding methods known as Otsu's (with the assumption of a...
Python Image Processing Cookbook
By :
Python Image Processing Cookbook
By:
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.
Related Content you might be interested in
Current Title:
Python Image Processing Cookbook
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
Other Books You May Enjoy
Customer Reviews