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OpenCV Articles
Page 8 of 11
Eroding an image using the OpenCV function erode()
In this program, we will erode an image using the OpenCV function erode(). Erosion of image means to shrink the image. If any of the pixels in a kernel is 0, then all the pixels in the kernel are set to 0. One condition before applying an erosion function on image is that the image should be a grayscale image.Original ImageAlgorithmStep 1: Import cv2 Step 2: Import numpy. Step 3: Read the image using imread(). Step 4: Define the kernel size using numpy ones. Step 5: Pass the image and kernel to the erode function. Step 6: Display the output.Example ...
Read MoreDraw a filled polygon using the OpenCV function fillPoly()
In this program, we will draw a filled polygon using the opencv function fillPoly(). The function takes in an image and the endpoints of the polygon.AlgorithmStep 1: Import cv2 and numpy. Step 2: Define the endpoints. Step 3: Define the image using zeros. Step 4: Draw the polygon using the fillpoly() function. Step 5: Display the output.Example Codeimport cv2 import numpy as np contours = np.array([[50,50], [50,150], [150,150], [150,50]]) image = np.zeros((200,200)) cv2.fillPoly(image, pts = [contours], color =(255,255,255)) cv2.imshow("filledPolygon", image)Output
Read MoreBlurring an image using the OpenCV function blur()
In this program, we will blur an image using the opencv function blur().AlgorithmStep 1: Import OpenCV. Step 2: Import the image. Step 3: Set the kernel size. Step 4: Call the blur() function and pass the image and kernel size as parameters. Step 5: Display the results.Original ImageExample Codeimport cv2 image = cv2.imread("testimage.jpg") kernel_size = (7,7) image = cv2.blur(image, kernel_size) cv2.imshow("blur", image)OutputBlurred ImageExplanationThe kernel size is used to blur only a small part of an image. The kernel moves across the entire image and blurs the pixels it covers.
Read MoreHow to detect and track the motion of eyeball in OpenCV using C++?
Here, we will learn how to detect and track the motion of eyeball in OpenCV.The following program demonstrates to detect the eyeball and track the location.Example#include #include #include #include #include #include using namespace cv; using namespace std; Vec3f eyeBallDetection(Mat& eye, vector& circles) { vectorsums(circles.size(), 0); for (int y = 0; y < eye.rows; y++) { uchar* data = eye.ptr(y); for (int x = 0; x < eye.cols; x++) { int pixel_value = static_cast(*data); for (int i = 0; i < circles.size(); i++) { ...
Read MoreHow to track the face in real-time in OpenCV using C++?
We will learn how to track the face in real-time in OpenCV. This program is same to the previous program and difference is that we used ellipse instead of rectangle to identify the face and we also used additional 'cout' statement to show the co-ordinate of the face in the console window.The following program to detect human face in real-time −Example#include #include #include //This header includes definition of 'rectangle()' function// #include //This header includes the definition of Cascade Classifier// #include using namespace std; using namespace cv; int main(int argc, char** argv) { Mat video_stream;//Declaring a matrix hold frames from ...
Read MoreHow to detect the largest face in OpenCV using C++?
We will learn how to detect the largest face only. This topic is same as the previous topic. The only difference is we used an additional 'Rect' structure and a 'for loop' to detect the largest face.The actual format of this function −Mat faceROI = image_with_humanface(maxRect)The maxRect have the area and location information of the largest face located on the image. The line above is cropping the same area stored in maxRect on the same location where the largest face is located on the image and storing in 'faceROI' matrix.The following program detects the largest face from still pictures −Example#include ...
Read MoreHow to crop the detected faces in OpenCV using C++?
We will know how to crop the detected faces in OpenCV. To crop detected faces, we need multiple matrices. The most appropriate way is to use an image array. In this program using the following two lines, we have declared two image matrices −Mat cropped_faces[4];Mat faceROI[4];The first matrix is to store the cropped images, and the second matrix is to define the region of interest. In the detection process, first, the program locates the faces and store them in vectors. In our program, the name of the vector is 'faces' Vectors can contain multiple elements.Using the following two lines, we ...
Read MoreHow to detect the face in still picture in OpenCV using C++?
We detect the faces from the image. To detect the face, we used 'detectMultiScale()' function.The actual format of this function is −SyntaxdetectMultiScale(source matrix, vector, searchScaleFactor, minNeighbours, flags, minfeatureSize)By changing the function arguments, we can control the 'detect.MultiSpace()' function. This function takes the following arguments.Source MatrixIt is the matrix where the face will be detected. In this case, it will the matrix which is keeping the video frames.VectorThe 'detect.MultiScale()' function will be a vector of rectangular type. A rectangle is a vector in OpenCV, and we have to define it as a vector.searchScaleFactorSearch scale factor determines how many different sizes of ...
Read MoreHow to detect the color using OpenCV in C++?
We will understand how to detect specific color and track object based on color. Performance of color detection and color detection based tracking system is environment dependent.If you change light of the room or if you change background color, there will be significant effect on color detection.The following program demonstrates how to detect the color using OpenCV in C++.Example#include #include #include using namespace std; using namespace cv; int main(int argc, char** argv) { VideoCapture video_load(0);//capturing video from default camera// namedWindow("Adjust");//declaring window to show the image// int Hue_Lower_Value = 0;//initial hue value(lower)// int Hue_Lower_Upper_Value = 22;//initial hue ...
Read MoreHow to rotate a video in OpenCV using C++?
Rotating a video is similar to rotate an image. The only difference is instead of load a still picture into an image matrix, we have loaded a video or take video stream from the camera.Here, we are not loading the video but taking a video using the camera. If you want to use a video file, just put the address of the video file properly.The following program demonstrates how to rotate a video in OpenCV using C++.Example#include #include #include using namespace std; using namespace cv; int main(int argc, char* argv[]) { VideoCapture loadvideo(0);//capture video from default camera// namedWindow("OriginalVideo");//declaring ...
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