我正在尝试获取位于这条曲线中间的一组点。 我找到了这个脚本,但我的激光图像不起作用...
im_gray = cv2.imread(img, cv2.CV_LOAD_IMAGE_GRAYSCALE)
im_gray = cv2.Canny(im_gray,50,150,apertureSize = 3)
ret, im_bw = cv2.threshold(im_gray, 0, 255, cv2.THRESH_BINARY)
#(thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
#thresh = 127
#im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]
#ret, bw = cv2.threshold(im_bw, 0, 255, cv2.THRESH_BINARY)
cv2.imwrite('resultpoint_bw.png',im_bw)
# find contours of the binarized image
contours, heirarchy = cv2.findContours(im_bw, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
# curves
curves = np.zeros((im_bw.shape[0], im_bw.shape[1], 3), np.uint8)
cv2.imwrite('resultpoint_bw_2.png',im_bw)
for i in range(len(contours)):
# for each contour, draw the filled contour
draw = np.zeros((im_bw.shape[0], im_bw.shape[1]), np.uint8)
cv2.drawContours(draw, contours, i, (255,255,255), -1)
# for each column, calculate the centroid
for col in range(draw.shape[0]):
M = cv2.moments(draw[:, col])
if M['m00'] != 0:
x = col
y = int(M['m01']/M['m00'])
curves[y, x, :] = (0, 0, 255)
cv2.imwrite('resultpoint_0.png',curves)
在结果图像中点是错误的,因为它是一个轮廓并且不需要轮廓但中间的单个点...
有没有可能做这个?
最佳答案
您可以应用这些简单的步骤来获得这条中心线。
- 阈值二进制反转
- 申请Thinning algorithm以减少厚度。
- 在二值图像中找到非零像素。
void thinningIteration(Mat& im, int iter)
{
Mat marker = Mat::zeros(im.size(), CV_8UC1);
for (int i = 1; i < im.rows-1; i++)
{
for (int j = 1; j < im.cols-1; j++)
{
uchar p2 = im.at<uchar>(i-1, j);
uchar p3 = im.at<uchar>(i-1, j+1);
uchar p4 = im.at<uchar>(i, j+1);
uchar p5 = im.at<uchar>(i+1, j+1);
uchar p6 = im.at<uchar>(i+1, j);
uchar p7 = im.at<uchar>(i+1, j-1);
uchar p8 = im.at<uchar>(i, j-1);
uchar p9 = im.at<uchar>(i-1, j-1);
int A = (p2 == 0 && p3 == 1) + (p3 == 0 && p4 == 1) +
(p4 == 0 && p5 == 1) + (p5 == 0 && p6 == 1) +
(p6 == 0 && p7 == 1) + (p7 == 0 && p8 == 1) +
(p8 == 0 && p9 == 1) + (p9 == 0 && p2 == 1);
int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
int m1 = iter == 0 ? (p2 * p4 * p6) : (p2 * p4 * p8);
int m2 = iter == 0 ? (p4 * p6 * p8) : (p2 * p6 * p8);
if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0)
marker.at<uchar>(i,j) = 1;
}
}
im &= ~marker;
}
void thinning(Mat& im)
{
im /= 255;
Mat prev = Mat::zeros(im.size(), CV_8UC1);
Mat diff;
do
{
thinningIteration(im, 0);
thinningIteration(im, 1);
absdiff(im, prev, diff);
im.copyTo(prev);
}
while (countNonZero(diff) > 0);
im *= 255;
}
void main()
{
Mat mSource_Bgr,mSource_Gray,mThreshold,mThinning;
mSource_Bgr= imread(FileName_S.c_str(),IMREAD_COLOR);
mSource_Gray= imread(FileName_S.c_str(),0);
threshold(mSource_Gray,mThreshold,50,255,THRESH_BINARY);
mThinning= mThreshold.clone();
thinning(mThinning);
imshow("mThinning",mThinning);
vector<Point2i> locations; // output, locations of non-zero pixels
findNonZero(mThinning, locations);
for (int i = 0; i < locations.size(); i++)
{
circle(mSource_Bgr,locations[i],2,Scalar(0,255,0),1);
}
imshow("mResult",mSource_Bgr);
}
关于java - opencv和python——激光曲线检测,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30478040/