Reader small image

You're reading from  OpenCV Computer Vision Application Programming Cookbook Second Edition

Product typeBook
Published inAug 2014
Reading LevelBeginner
PublisherPackt
ISBN-139781782161486
Edition1st Edition
Languages
Tools
Right arrow
Author (1)
Robert Laganiere
Robert Laganiere
author image
Robert Laganiere

Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content based video analysis, visual surveillance, driver-assistance, object detection, and tracking. Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001. He co-founded Visual Cortek in 2006, an Ottawa-based video analytics start-up that was later acquired by iwatchlife.com in 2009. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of start-up companies such as Cognivue Corp, iWatchlife, and Tempo Analytics. Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and MSc and PhD degrees from INRS-Telecommunications, Montreal (1996). You can visit the author's website at laganiere.name.
Read more about Robert Laganiere

Right arrow

Introduction


In order to build computer vision applications, you need to be able to access the image content and eventually modify or create images. This chapter will teach you how to manipulate the picture elements (also known as pixels). You will learn how to scan an image and process each of its pixels. You will also learn how to do this efficiently, since even images of modest dimensions can contain hundreds of thousands of pixels.

Fundamentally, an image is a matrix of numerical values. This is why, as we learned in Chapter 1, Playing with Images, OpenCV 2 manipulates them using the cv::Mat data structure. Each element of the matrix represents one pixel. For a gray-level image (a black-and-white image), pixels are unsigned 8-bit values where 0 corresponds to black and 255 corresponds to white. In the case of color images, three primary color values are required in order to reproduce the different visible colors. This is a consequence of the fact that our human visual system is trichromatic...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
OpenCV Computer Vision Application Programming Cookbook Second Edition
Published in: Aug 2014Publisher: PacktISBN-13: 9781782161486

Author (1)

author image
Robert Laganiere

Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content based video analysis, visual surveillance, driver-assistance, object detection, and tracking. Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development published by McGraw Hill in 2001. He co-founded Visual Cortek in 2006, an Ottawa-based video analytics start-up that was later acquired by iwatchlife.com in 2009. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of start-up companies such as Cognivue Corp, iWatchlife, and Tempo Analytics. Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and MSc and PhD degrees from INRS-Telecommunications, Montreal (1996). You can visit the author's website at laganiere.name.
Read more about Robert Laganiere