Open Source Computer Vision Library https://opencv.org/
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2.1 KiB

Feature Detection

Goal

In this tutorial you will learn how to:

  • Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically:
    • Use the @ref cv::SurfFeatureDetector and its function @ref cv::detect to perform the detection process
    • Use the function @ref cv::drawKeypoints to draw the detected keypoints

Theory

Code

This tutorial code's is shown lines below. @code{.cpp} #include <stdio.h> #include #include "opencv2/core.hpp" #include "opencv2/features2d.hpp" #include "opencv2/xfeatures2d.hpp" #include "opencv2/highgui.hpp"

using namespace cv; using namespace cv::xfeatures2d;

void readme();

/* @function main / int main( int argc, char* argv ) { if( argc != 3 ) { readme(); return -1; }

Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE ); Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );

if( !img_1.data || !img_2.data ) { std::cout<< " --(!) Error reading images " << std::endl; return -1; }

//-- Step 1: Detect the keypoints using SURF Detector int minHessian = 400;

Ptr detector = SURF::create( minHessian );

std::vector keypoints_1, keypoints_2;

detector->detect( img_1, keypoints_1 ); detector->detect( img_2, keypoints_2 );

//-- Draw keypoints Mat img_keypoints_1; Mat img_keypoints_2;

drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT ); drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );

//-- Show detected (drawn) keypoints imshow("Keypoints 1", img_keypoints_1 ); imshow("Keypoints 2", img_keypoints_2 );

waitKey(0);

return 0; }

/* @function readme */ void readme() { std::cout << " Usage: ./SURF_detector " << std::endl; } @endcode Explanation

Result

  1. Here is the result of the feature detection applied to the first image:

    image

  2. And here is the result for the second image:

    image