Digital image processing using OpenCV in c++

Posted on 21 Nov 10:59 | by mitsumi | 13 views
Digital image processing using OpenCV  in c++

Published 11/2022
Created by Ezeuko Emmanuel
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 17 Lectures ( 3h 36m ) | Size: 1.38 GB


Image processing technique using OpenCV in C++


What you'll learn
The student will learn how to open, display , manipulate and store image pixels using the OPENCV library in C++
The student will learn how to manipulate 2D and 3D matrix pointer array
The code used in this course is very flexible and openCV can easily be replaced by anyother image library in C++
The student will learn how to apply logic operations on images in C++ including logicAnd, logicOr, logicXor
The student will also be able to implement all these technique listed above without the use of openCV library or other C++ libraries
The student will learn how to binarize images using Otsu technique for thresholding
The student will be able to implement filters on images using convolution e.g sobel filter, gauss filter, prewitt filter, edge detection, etc
Other C++ image processing technique to learn will include contrast saturation, histogram equalization, scaling and brightening of image
Requirements
Basic knowledge of C++ is required
Description
Welcome, In this course you will learn digital image using the C++ language. We will implement 23 image processing technique from scratch without the use of any external libraries. However, C++ does not have the capacity to open and read image pixels. Therefore we use openCV in this course to open an image, read its pixel, and display a new image. This makes this course very flexible as any alternative library can be used to perform this simple task while leaving you with the bulk of the job to build from scratch.By the end of the lesson, the student will be able to manipulate image pixels, by changing their colour intensities , forming new images from pre-existing images,  store image pixels using a 2D and 3D pointer array stored within the image class, some of the technique we will implement will include:luminanceConvolution linear contrastEdge detectionOtsu binarizationimage sharpeningImage thresholdingGray Scale conversionhistogram equalizationLeft rotate, Right rotate linear contrast saturationvertical flip, horizontal flip Filtering ( Instagram filter) sharpening, Laplacien convoimage addition, image subtraction Adjusting brightness and contrast logical And, logical Or, logical Xor, logical NandScaling image (increasing and decreasing the size of an image)Erosion, Prewitt filter, Sobel filter, Gauss filter, Robert filter, smoothening filter,
Who this course is for
All levels C++ developer

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