BRISK特征点
2011年提出,是一种二进制的特征描述算子。速度比较:SIFT<SURF<BRISK<FREAK<ORB,在对有较大模糊的图像配准时,BRISK算法在其中表现最为出色。
【函数】
Ptr<BRISK> create(int thresh=30, int octaves=3, float patternScale=1.0f);
【参数说明】原理链接
thresh——AGAST检测阈值
octaves——octave层数,0则单尺度
patternScale——关键点邻域采样倍数,多尺度空间下采样的倍数
【案例】
#include <opencv2/opencv.hpp> #include <iostream> using namespace std; using namespace cv; int main() { Mat srcImage = imread("D:/sunflower.png"); Mat srcGrayImage; if (srcImage.channels() == 3) { cvtColor(srcImage,srcGrayImage,CV_RGB2GRAY); } else { srcImage.copyTo(srcGrayImage); } vector<KeyPoint>detectKeyPoint; Mat keyPointImage1,keyPointImage2; Ptr<BRISK> brisk = BRISK::create(); brisk->detect(srcGrayImage,detectKeyPoint); drawKeypoints(srcImage,detectKeyPoint,keyPointImage1,Scalar(0,0,255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS); drawKeypoints(srcImage,detectKeyPoint,keyPointImage2,Scalar(0,0,255),DrawMatchesFlags::DEFAULT); imshow("src image",srcImage); imshow("keyPoint image1",keyPointImage1); imshow("keyPoint image2",keyPointImage2); waitKey(0); return 0; }