Image processing technique using OpenCV in C++
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.
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.
Course Content
- Introduction –> 18 lectures • 3hr 43min.
Requirements
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:
luminance
Convolution
linear contrast
Edge detection
Otsu binarization
image sharpening
Image thresholding
Gray Scale conversion
histogram equalization
Left rotate, Right rotate
linear contrast saturation
vertical flip, horizontal flip
Filtering ( Instagram filter)
sharpening, Laplacien convo
image addition, image subtraction
Adjusting brightness and contrast
logical And, logical Or, logical Xor, logical Nand
Scaling image (increasing and decreasing the size of an image)
Erosion, Prewitt filter, Sobel filter, Gauss filter, Robert filter, smoothening filter,