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c++ - OpenCV 圆形形状检测及其面积

转载 作者:塔克拉玛干 更新时间:2023-11-03 01:27:03 37 4
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enter image description here我有一个像圆形的图像,其中包含另一个类似的形状。我正在尝试找到这两个形状的区域。我正在使用 openCv c++ 霍夫圆检测,但它没有检测到形状。 OpenCV中有没有其他函数可以用来检测形状和找到区域?

[编辑] 图片已添加。

这是我的示例代码

int main()
{
Mat src, gray;
src = imread( "detect_circles_simple.jpg", 1 );resize(src,src,Size(640,480));
cvtColor( src, gray, CV_BGR2GRAY );
// Reduce the noise so we avoid false circle detection
GaussianBlur( gray, gray, Size(9, 9), 2, 2 );

vector<Vec3f> circles;

// Apply the Hough Transform to find the circles
HoughCircles( gray, circles, CV_HOUGH_GRADIENT, 1, 30, 200, 50, 0, 0 );
cout << "No. of circles : " << circles.size()<<endl;
// Draw the circles detected
for( size_t i = 0; i < circles.size(); i++ )
{
Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 );// circle center
circle( src, center, radius, Scalar(0,0,255), 3, 8, 0 );// circle outline
cout << "center : " << center << "\nradius : " << radius << endl;
}
exit(0);
// Show your results
namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE );
imshow( "Hough Circle Transform Demo", src );

waitKey(0);
return 0;
}

最佳答案

我有一个类似的方法。

img1 = cv2.imread('disc1.jpg', 1)
img2 = img1.copy()
img = cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)

#--- Blur the gray scale image
img = cv2.GaussianBlur(img,(5, 5),0)

#--- Perform Canny edge detection (in my case lower = 84 and upper = 255, because I resized the image, may vary in your case)
edges = cv2.Canny(img, lower, upper)
cv2.imshow('Edges', edges )

enter image description here

#---Find and draw all existing contours
_, contours , _= cv2.findContours(edges, cv2.RETR_TREE, 1)
rep = cv2.drawContours(img1, contours, -1, (0,255,0), 3)
cv2.imshow(Contours',rep)

enter image description here

由于您正在分析圆形边缘的形状,因此确定轮廓的偏心率在这种情况下会有所帮助。

#---Determine eccentricity
cnt = contours
for i in range(0, len(cnt)):
ellipse = cv2.fitEllipse(cnt[i])
(center,axes,orientation) =ellipse
majoraxis_length = max(axes)
minoraxis_length = min(axes)
eccentricity=(np.sqrt(1-(minoraxis_length/majoraxis_length)**2))
cv2.ellipse(img2,ellipse,(0,0,255),2)

cv2.imshow('Detected ellipse', img2)

enter image description here

现在根据 eccentricity 变量给出的值,您可以得出轮廓是否为圆形的结论。阈值取决于您认为什么是圆形或近似圆形。

关于c++ - OpenCV 圆形形状检测及其面积,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/42907613/

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