fanfuhan OpenCV 教學096 ~ opencv-096-描述子比對/匹配

資料來源: https://fanfuhan.github.io/

https://fanfuhan.github.io/2019/05/10/opencv-096/

GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV

圖像特徵檢測首先會獲取關鍵點，然後根據關鍵點周圍的ROI區域的大小，生成描述子，完整的描述子向量就表示了一張圖像的特徵，是圖像特徵數據，這種方式也被稱為圖像特徵工程，即通過先驗模型與合理計算得到圖像特徵數據的過程，有了特徵數據我們就可以利用特徵數據實現對象檢測與對象識別，這個最簡單的方法就是特徵匹配，OPenCV提供了兩種圖像特徵匹配的算法

  ~暴力匹配
  ~FLANN匹配

其中FLANN是一種高效的數值或二進制匹配算法，SIFT / SURF是基於浮點數的匹配，ORB是二值匹配，速度轉換。 HASH。這個在C ++的代碼種編寫而成的演示。暴力匹配在Python代碼種做了演示。對匹配之後的輸出結果，根據距離進行排序，就會得到距離比較的匹配點，這個才是好的特徵匹配。

C++

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
#define RATIO    0.4
using namespace cv;
using namespace std;

int main(int argc, char** argv) {
	Mat box = imread("D:/images/box.png");
	Mat scene = imread("D:/images/box_in_scene.png");
	if (scene.empty()) {
		printf("could not load image...\n");
		return -1;
	}
	imshow("input image", scene);
	vector<KeyPoint> keypoints_obj, keypoints_sence;
	Mat descriptors_box, descriptors_sence;
	Ptr<ORB> detector = ORB::create();
	detector->detectAndCompute(scene, Mat(), keypoints_sence, descriptors_sence);
	detector->detectAndCompute(box, Mat(), keypoints_obj, descriptors_box);

	vector<DMatch> matches;
	// ��ʼ��flannƥ��
	// Ptr<FlannBasedMatcher> matcher = FlannBasedMatcher::create(); // default is bad, using local sensitive hash(LSH)
	Ptr<DescriptorMatcher> matcher = makePtr<FlannBasedMatcher>(makePtr<flann::LshIndexParams>(12, 20, 2));
	matcher->match(descriptors_box, descriptors_sence, matches);

	// ����ƥ��
	vector<DMatch> goodMatches;
	printf("total match points : %d\n", matches.size());
	float maxdist = 0;
	for (unsigned int i = 0; i < matches.size(); ++i) {
		printf("dist : %.2f \n", matches[i].distance);
		maxdist = max(maxdist, matches[i].distance);
	}
	for (unsigned int i = 0; i < matches.size(); ++i) {
		if (matches[i].distance < maxdist*RATIO)
			goodMatches.push_back(matches[i]);
	}

	Mat dst;
	drawMatches(box, keypoints_obj, scene, keypoints_sence, goodMatches, dst);
	imshow("output", dst);

	waitKey(0);
	return 0;
}

Python

"""
描述子匹配
"""

import cv2 as cv

box = cv.imread("images/box.png")
box_in_scene = cv.imread("images/box_in_scene.png")
cv.imshow("box", box)
cv.imshow("box_in_scene", box_in_scene)

# 创建ORB特征检测器
orb = cv.ORB_create()

# 得到特征关键点和描述子
kp1, des1 = orb.detectAndCompute(box, None)
kp2, des2 = orb.detectAndCompute(box_in_scene, None)

# 暴力匹配
bf = cv.BFMatcher(cv.NORM_HAMMING, crossCheck=True)
matchers = bf.match(des1, des2)

# 绘制匹配
matchers = sorted(matchers, key=lambda x: x.distance)
result = cv.drawMatches(box, kp1, box_in_scene, kp2, matchers[:15], None)
cv.imshow("orb-match", result)

cv.waitKey(0)
cv.destroyAllWindows()