Target Detection program Development (IV.)--Target detection

Met a good "OpenCV introductory tutorial" http://www.opencv.org.cn/forum.php?mod=viewthread&tid=33549

An introduction to the operations that contain the matrix classes and their memory management

And the operation of reading and writing images and videos.

An example

#include <iostream>
#include "opencv2/opencv.hpp"

using namespace std;
using namespace CV;
int main () {

	
	cascadeclassifier classifier;//classifier
	classifier.load ("E:\\training\\result\\cascade.xml");// Load classifier

	Mat img = imread ("E:\\training\\result\\1.jpg", 0);//The image to be detected, 0 to convert to grayscale figure
	
	vector<rect> faces;// Save the rectangle of the identified target
	//The last two parameters are the minimum size and maximum size of the scan window
	Classifier.detectmultiscale (IMG, faces, 1.1, 2, 0 | Cv_haar_scale_image, Size (+));
	if (Faces.empty ()) {
		imshow ("Test", IMG);

		Waitkey (0);
		return 0;
	}
	else{
		//mark the Recognized object//
		Compute Center Point
		Center (faces[0].x + FACES[0].WIDTH/2, faces[0].y + FACES[0].HEIGHT/2); c19/>//draws the ellipse
		ellipse (IMG, center, Size (Faces[0].width, faces[0].height),
			0, 255, 0, Scalar (0), 1, 1); c22/>//Display picture
		imshow ("Test", IMG);

		Waitkey (0);
		return 0;
	}
	
}

Detectmultiscale This method is very slow,,, scan again I use 50x50 only scan 1 times have to 1s time, basically not reach the application requirements, should consider the actual situation of the problem, self-rewriting the method of detection, such as more accurately limit the size of the scan window, narrow the scope of the scan, Do parallel scanning and so on optimization measures.