Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
12
Index

Computing the image histogram


An image is made of pixels, and each of them have different values. For example, in a 1-channel gray-level image, each pixel has a value between 0 (black) and 255 (white). Depending on the picture content, you will find different amounts of each gray shade laid out inside the image.

A histogram is a simple table that gives you the number of pixels that have a given value in an image (or sometimes, a set of images). The histogram of a gray-level image will, therefore, have 256 entries (or bins). Bin 0 gives you the number of pixels that have the value 0, bin 1 gives you the number of pixels that have the value 1, and so on. Obviously, if you sum all of the entries of a histogram, you should get the total number of pixels. Histograms can also be normalized such that the sum of the bins equals 1. In this case, each bin gives you the percentage of pixels that have this specific value in the image.

Getting started

The first three recipes of this chapter will use the...