OpenCV C++ Guided project tutorial (digital image processing

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Ezeuko Emmanuel

3:36:04

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1. 01. Introduction to digital Image processing.mp4

04:30

2.1 dim.zip

2. download project files here.html

3. Q&A.mp4

00:58

4. 02. How to use pointers to store image pixels for both coloured and gray scale.mp4

06:48

5. 03. How to set and retrieve the pixel value at a particular location in an image.mp4

15:32

6. 04. How does pixels arranged in a matrix form an Image.mp4

14:59

7. 05. Declaring the list of image processing technique.mp4

17:16

8. 06. How to read an image and extract pixels into a matrix using openCV.mp4

12:41

9. 07. How to convert to gray scale and also pixels into an image using openCV.mp4

15:51

10. 08. Horizontal and vertical flipping on an image.mp4

16:29

11. 09. How to left rotate and right rotate an image matrix.mp4

09:44

12. 10. How does Image thresholding and Otsu Binarization.mp4

20:13

13. 11. Implementation of Otsu Binarization to Image thresholding.mp4

17:48

14. 12, Logical operation logical And, logical Or, logical Xor, logical Nand.mp4

15:54

15. 13. Linear contrast saturation, scaling image, brightness,histogram equalization.mp4

19:59

16. 14. How iconvolution is implemented on an image matrix using a kernel.mp4

15:13

17. 15. convolution on filters.mp4

12:09

Description

Image processing technique using OpenCV in C++ (Guided project)

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

Who is this for?

All levels C++ developer

More details

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,Â 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,
Who this course is for:
All levels C++ developer

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With over 7years designing vhdl, verilog projects on fpga.Emmanuel is an embedded c++ system developer. He has strong knowledge in FPGA (Field Programmable Gate Array) development, Digital Electronics, Circuit Board design, and VHDL design and modeling of hardware systems using Logism. His focus of study in school was embedded systems with specialization in soc system on chip, processor core, serial communication protocols and encryption.

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