In this chapter, we played with image colors. We used different color spaces and tried to identify image areas that have a specific color. The RGB color space, for instance, was considered, and although it is an effective representation for the capture and display of colors in electronic imaging systems, this representation is not very intuitive. This is not the way humans think about colors. We talk about colors in terms of their tint, brightness, or colorfulness (that is, whether it is a vivid or pastel color). The phenomenal color spaces based on the concept of hue, saturation, and brightness were introduced to help users to specify the colors using properties that are more intuitive to them. In this recipe, we will explore the concepts of hue, saturation, and brightness as a means to describe colors.

OpenCV Computer Vision Application Programming Cookbook
By :

OpenCV Computer Vision Application Programming Cookbook
By:
Overview of this book
Table of Contents (18 chapters)
OpenCV Computer Vision Application Programming Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Playing with Images
Manipulating Pixels
Processing Color Images with Classes
Counting the Pixels with Histograms
Transforming Images with Morphological Operations
Filtering the Images
Extracting Lines, Contours, and Components
Detecting Interest Points
Describing and Matching Interest Points
Estimating Projective Relations in Images
Processing Video Sequences
Index
Customer Reviews