我想通过使用SimpleBlobDetection检测音乐人员的圆圈/椭圆,但是当我尝试检测它们时,它会在图片上找到不相关的点。
原始图片:
Blob检测后:
请参阅以下代码:
cv::SimpleBlobDetector::Params params;
//Thresholds
params.minThreshold = 10;
params.maxThreshold = 200;
// Filter by Area
params.filterByArea = true;
params.minArea = 100;
params.maxArea = 500;
// Filter by Circularity
params.filterByCircularity = true;
params.minCircularity = 0.1;
params.maxCircularity = 0.5;
// Filter by Convexity
params.filterByConvexity = true;
params.minConvexity = 0.57;
params.maxConvexity = 0.97;
// Filter by Inertia
params.filterByInertia = true;
params.minInertiaRatio = 0.01;
// set up and create the detector using the parameters
cv::SimpleBlobDetector blob_detector(params);
// detect!
vector<cv::KeyPoint> keypoints;
blob_detector.detect(tresh, keypoints);
// extract the x y coordinates of the keypoints:
for (int i = 0; i < keypoints.size(); i++){
float X = keypoints[i].pt.x;
float Y = keypoints[i].pt.y;
circle(tresh, Point(X, Y), 1, Scalar(0, 255, 0), 3, CV_AA);
}
imshow("Detected Blobs", tresh);
请帮帮我......
答案 0 :(得分:0)
如何使用Hough transform检测圈子?
答案 1 :(得分:0)
您是否尝试过不同的过滤器值(尤其是最小/最大区域 - 这些是平方值)?那么,应用颜色过滤(即仅白色)呢?
答案 2 :(得分:0)
这是解决方案。我从SimpleBlobDetector Tutorial复制了它
# Standard imports
import cv2
import numpy as np;
# Read image
im = cv2.imread("blob.jpg", cv2.IMREAD_GRAYSCALE)
im_orig = im
_, im = cv2.threshold(im, 128, 255, cv2.THRESH_BINARY)
im = 255 - im;
im = 255 - cv2.erode(im, np.ones((3,3)), iterations=2)
# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()
# Filter by Area.
params.filterByArea = True
params.minArea = 20
params.filterByConvexity = False
# Create a detector with the parameters
ver = (cv2.__version__).split('.')
if int(ver[0]) < 3 :
detector = cv2.SimpleBlobDetector(params)
else :
detector = cv2.SimpleBlobDetector_create(params)
# Detect blobs.
keypoints = detector.detect(im)
# Draw blobs
im_with_keypoints = cv2.drawKeypoints(im_orig, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
#Write image
cv2.imwrite("treble_staff.jpg", im_with_keypoints)
# Show blobs
cv2.imshow("Keypoints", im_with_keypoints)
cv2.waitKey(0)