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OpenCV-Python 双目相机标定和立体匹配
OpenCV-Python 相机标定及矫正,张正友相机标定法
双目立体视觉是计算机视觉范畴的核心之一,它利用双目相机来获得目标物体的图像,经过物体图像处理 之后得到目标物体所在场景环境的三维信息,最终实现非接触条件下测距,简单便捷。本次毕业设计主要内容为研究 基于双目立体视觉平台上的图像匹配以及目标物体的距离测量技术,图像特征提取部分研究了 SIFT 算法和 SURF 算 法,特征匹配部分研究了 BF 法和 FLANN 法,距离测量研究主要通过视差深度的计算,结合视觉坐标系的转换实现 三维位置的定位与测量。结合维视双目立体视觉测量平台 MV-VS220,通过 Python+OpenCV 设计实现一个具备图像 采集、图像匹配以及距离测量等功能的原型演示系统。系统可实现对关键环节的过程与结果的演示,以及不同算法的 性能比较。系统测试表明,所开发的原型演示系统从界面、功能与性能方面均达到了设计的要求。
该资源为作者在CSDN的撰写Python图像处理文章的支撑,主要是Python实现图像处理、图像识别、图像分类等算法代码实现,希望该资源对您有所帮助,一起加油。
基于Opencv的车道线检测:1. 图像加载;2.图像预处理:图片灰度化,高斯滤波;3.Cany边缘检测;4.感兴趣区域检测;5.霍夫直线检测 ;6.直线拟合;7.车道线叠加;8.图片和视频测试;9.可视化界面pyqt5 (可选)。
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张正友标定法的数学原理以及python源码实现(详细)
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