角点检测概述

角点检测概述

Harris角点检测算法手动实现

Harris角点检测算法手动实现

opencv中使用Harris角点检测

opencv中使用Harris角点检测

opencv中使用 Shi-Tomasi角点检测

函数：corners = cv.goodFeaturesToTrack( image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]] )
image：源图像
maxCorners：角点数
qualityLevel：质量等级
minDistance：角点之间最小距离

实验：使用Shi-Tomasi检测图像角点

import cv2 as cv
import numpy as np

img = cv.imread(‘qiqiao.jpg‘)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

# Shi-Tomasi角点检测
corners = cv.goodFeaturesToTrack(gray, 12, 0.01, 10)
corners = np.int0(corners)  # 12个角点坐标

for i in corners:
    # 压缩至一维：[[62,64]]->[62,64]
    x, y = i.ravel()
    cv.circle(img, (x, y), 4, (0, 0, 255), -1)

cv.imshow(‘dst‘, img)
cv.waitKey(0)

opencv 实现角点检测 Shi-Tomasi角点检测

原文：https://www.cnblogs.com/wojianxin/p/12625777.html