11、图像检索与目标检测技术全解析

图像检索与目标检测技术全解析

1. FLANN匹配与单应性变换

单应性变换（Homography）是计算机视觉中一个重要的概念。简单来说，当一个图形是另一个图形的透视变形时，它们之间就存在单应性。下面通过代码示例来详细说明如何利用FLANN（Fast Library for Approximate Nearest Neighbors）匹配结合单应性变换进行图像匹配。

import numpy as np
import cv2
from matplotlib import pyplot as plt

MIN_MATCH_COUNT = 10
img1 = cv2.imread('images/bb.jpg', 0)
img2 = cv2.imread('images/color2_small.jpg', 0)

sift = cv2.xfeatures2d.SIFT_create()
kp1, des1 = sift.detectAndCompute(img1, None)
kp2, des2 = sift.detectAndCompute(img2, None)

FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
search_params = dict(checks=50)
flann = cv2.FlannBasedMatcher(index_params, search_params)
matches = flann.knnMatch(des1, des2, k=2)

# store all the good mat