OpenCV for Robotics

Object tracking
Robot navigation
Face detection

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Filter Images and Videos

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In the image process the image filtering is a neighborhood operation in which the value of any given pixel in the output image is determined by applying a certain algorithm to the pixel values ​​in the vicinity of the corresponding input pixel . This technique is commonly used to smooth, sharpen and detect edges of images and videos. Filtering:   neighborhood operation   pixel algorithm to the pixel values ​​in the vicinity of the corresponding input pixel . smooth, sharpen and detect edges of images and videos. Example Algorithms  Mean Filter Weighted Average Filter Median Filter Min Filter Max Filter Inbuilt functions: blur : function blur(image, image_blurred_with_3x3_kernel, Size(3, 3)); blur(image, image_blurred_with_5x5_kernel, Size(5, 5));         String window_name = "The Guitar"; String window_name_blurred_with_3x3_kernel = "The Guitar Blurred with 3 x 3 Kernel"; S...
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Create Tranck Bar:

        Mat src = imread("MyPic.JPG");         namedWindow("My Window", 1);         int iSliderValue1 = 50; createTrackbar("Brightness", "My Window", & iSliderValue1 , 100); int iSliderValue2 = 50; createTrackbar("Contrast", "My Window", & iSliderValue2 , 100);                  Mat dst;          src .convertTo(dst, -1, dContrast, iBrightness);         imshow("My Window", dst);          IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII //Uncomment the following line if you are compiling this code in Visual Studio #include "stdafx.h" #include <opencv2/opencv.hpp> #include <iostream> #include <opencv2/cv.h> #include <opencv2/highgui.h> using namespace cv; using namespace std; /// Global Variables const int ...
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OpenCV Programming 1

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