Tutorial by Examples

To access pixel values in an OpenCV cv::Mat object, you first have to know the type of your matrix. The most common types are: CV_8UC1 for 8-bit 1-channel grayscale images; CV_32FC1 for 32-bit floating point 1-channel grayscale images; CV_8UC3 for 8-bit 3-channel color images; and CV_32FC3 ...

If efficiency is important, a fast way to iterate over pixels in a cv::Mat object is to use its ptr<T>(int r) method to obtain a pointer to the beginning of row r (0-based index). According to the matrix type, the pointer will have a different template. For CV_8UC1: uchar* ptr = image.ptr&...

// PixelAccessTutorial.cpp : Defines the entry point for the console // Environment: Visual studio 2015, Windows 10 // Assumptions: Opecv is installed configured in the visual studio project // Opencv version: OpenCV 3.1 #include "stdafx.h" #include<opencv2/core/core.hpp> #i...

It's not the best way of iterating through the pixels; however, it's better than cv::Mat::at<T>. Let's assume you have a color image in your folder and you want to iterate each pixels of this image and erase green and red channels(Note that this is an example, you can do this in more optimize...

Individual pixel access in OpenCV Mat structure can be achieved in multiple ways. To understand how to access, it is better to learn the data types first. Basic Structures explains the basic datatypes. Shortly, CV_<bit-depth>{U|S|F}C(<number_of_channels>) is the basic structure of a typ...