Python opencv 图像相似度匹配之ORB+KNN

原文地址：https://www.cnblogs.com/Lin-Yi/p/9433942.html

代码如下：

# coding:utf-8

import cv2

# 按照灰度图像读入两张图片
img1 = cv2.imread("../data/logo1.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("../data/album1.png", cv2.IMREAD_GRAYSCALE)

# 获取特征提取器对象
orb = cv2.ORB_create()
# 检测关键点和特征描述
keypoint1, desc1 = orb.detectAndCompute(img1, None)
keypoint2, desc2 = orb.detectAndCompute(img2, None)
"""
keypoint 是关键点的列表
desc 检测到的特征的局部图的列表
"""
# 获得knn检测器
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
matches = bf.knnMatch(desc1, desc2, k=1)
"""
knn 匹配可以返回k个最佳的匹配项
bf返回所有的匹配项
"""
# 画出匹配结果
img3 = cv2.drawMatchesKnn(img1, keypoint1, img2, keypoint2, matches, img2, flags=2)
cv2.imshow("matches", img3)
cv2.waitKey()
cv2.destroyAllWindows()