opencv: SimpleBlobDetector 使用

最新推荐文章于 2022-06-17 13:41:42 发布

hustbk

最新推荐文章于 2022-06-17 13:41:42 发布

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本文链接：https://blog.youkuaiyun.com/hustbk/article/details/43410277

本文介绍了一个使用简单Blob检测器进行特征点检测的过程。详细配置了检测器的各项参数，如阈值设置、颜色筛选、面积范围等，并展示了检测时间和检测到的关键点数量。

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Mat image = GetDocument()->image;
vector<KeyPoint> keyPoints;
SimpleBlobDetector::Params params;

params.thresholdStep = 10;
params.minThreshold = 50;
params.maxThreshold = 220;
params.minRepeatability = 2;
params.minDistBetweenBlobs = 10;

params.filterByColor = true;
params.blobColor = 255;

params.filterByArea = true;
params.minArea = 25;
params.maxArea = 5000;

params.filterByCircularity = false;
params.minCircularity = 0.8f;
params.maxCircularity = std::numeric_limits<float>::max();

params.filterByInertia = false;
//minInertiaRatio = 0.6;
params.minInertiaRatio = 0.1f;
params.maxInertiaRatio = std::numeric_limits<float>::max();

params.filterByConvexity = true;
//minConvexity = 0.8;
params.minConvexity = 0.95f;
params.maxConvexity = std::numeric_limits<float>::max();

double tt=getTickCount();

Ptr<SimpleBlobDetector> blobDetect=SimpleBlobDetector::create(params);
blobDetect->detect(image, keyPoints);

OutInfo("SimpleBlobDetector time",(getTickCount()-tt)*1000/getTickFrequency());

OutInfo("keypoints count",(long)keyPoints.size());

drawKeypoints(image, keyPoints, image, Scalar(0,255,0));
namedWindow("blobs");

imshow("blobs", image);