如何检测视频中的形状?

时间:2014-04-14 18:38:37

标签: c++ opencv

我已经编写了这个检测视频中不同形状的形状检测代码,当被检测物体静止但在物体移动时没有检测到形状时,代码效果很好,因为无法从中找到轮廓。在物体移动的同时。我已经尝试了一切来解决这个问题,但我还没有找到解决方案。有人可以帮我弄清楚如何解决这个问题,谢谢你提前。代码如下。

/**
* Simple shape detector program.
* It loads an image and tries to find simple shapes (rectangle, triangle, circle, etc) in it.
* This program is a modified version of `squares.cpp` found in the OpenCV sample dir.
*/
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <cmath>
#include <iostream>
#include <sstream>
#include <string>
#include <iostream>
#include <opencv/highgui.h>
#include <opencv/cv.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <fcntl.h>
#include <stdio.h>
#include <unistd.h>

/**
* Helper function to find a cosine of angle between vectors
* from pt0->pt1 and pt0->pt2
*/
static double angle(cv::Point pt1, cv::Point pt2, cv::Point pt0)
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

/**
* Helper function to display text in the center of a contour
*/
void setLabel(cv::Mat& im, const std::string label, std::vector<cv::Point>& contour)
{
int fontface = cv::FONT_HERSHEY_SIMPLEX;
double scale = 0.4;
int thickness = 1;
int baseline = 0;

cv::Size text = cv::getTextSize(label, fontface, scale, thickness, &baseline);
cv::Rect r = cv::boundingRect(contour);

cv::Point pt(r.x + ((r.width - text.width) / 2), r.y + ((r.height + text.height) / 2));
cv::rectangle(im, pt + cv::Point(0, baseline), pt + cv::Point(text.width, -text.height), CV_RGB(255,255,255), CV_FILLED);
cv::putText(im, label, pt, fontface, scale, CV_RGB(0,0,0), thickness, 8);
}

int main()
{
    //cvNamedWindow("Camera_Output", 1); //Create window
CvCapture* capture = cvCaptureFromCAM(2); //Capture using any camera connected to your system

while(1){
IplImage * img = cvQueryFrame(capture); 

//show the original image
//cvNamedWindow("Raw");
//cvShowImage("Raw",img);


cv::Mat src(img);

//cv::Mat src = cv::imread("/home/john/Desktop/basic-shapes.png");
//if (src.empty())
//return -1;

// Convert to grayscale
cv::Mat gray;
cv::cvtColor(src, gray, CV_BGR2GRAY);

// Use Canny instead of threshold to catch squares with gradient shading
cv::Mat bw;
cv::Canny(gray, bw, 0, 50, 5);

// Find contours
std::vector<std::vector<cv::Point> > contours;
cv::findContours(bw.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

std::vector<cv::Point> approx;
cv::Mat dst = src.clone();

for (int i = 0; i < contours.size(); i++)
{
// Approximate contour with accuracy proportional
// to the contour perimeter
cv::approxPolyDP(cv::Mat(contours[i]), approx, cv::arcLength(cv::Mat(contours[i]), true)*0.02, true);

// Skip small or non-convex objects
if (std::fabs(cv::contourArea(contours[i])) < 1000 || !cv::isContourConvex(approx))
continue;


if (approx.size() >= 4 && approx.size() <= 6)
{
// Number of vertices of polygonal curve
int vtc = approx.size();

// Get the cosines of all corners
std::vector<double> cos;
for (int j = 2; j < vtc+1; j++)
cos.push_back(angle(approx[j%vtc], approx[j-2], approx[j-1]));

// Sort ascending the cosine values
std::sort(cos.begin(), cos.end());


// Use the degrees obtained above and the number of vertices
// to determine the shape of the contour
if (vtc == 4)
setLabel(dst, "RECT", contours[i]);
else if (vtc == 5 )
setLabel(dst, "PENTA", contours[i]);
else if (vtc == 6 )
setLabel(dst, "HEXA", contours[i]);
}
else
{
// Detect and label circles
double area = cv::contourArea(contours[i]);
cv::Rect r = cv::boundingRect(contours[i]);
int radius = r.width / 2;

if (std::abs(1 - ((double)r.width / r.height)) <= 0.2 &&
std::abs(1 - (area / (CV_PI * std::pow(radius, 2)))) <= 0.2)
setLabel(dst, "CIR", contours[i]);
}
}

//cv::imshow("src", src);
cv::imshow("dst", dst);
cv::waitKey(10);
}

return 0;
}

0 个答案:

没有答案