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XuetangX

图像采集与处理

Beijing Institute of Technology via XuetangX

Overview

Learn the fundamentals and advanced concepts of image acquisition and processing in this comprehensive Chinese language course. Master essential topics from image acquisition systems including camera sensors and lenses to sophisticated image preprocessing techniques like enhancement, edge detection, and various filtering methods. Explore object detection through multiple approaches including threshold segmentation, motion information, optical flow, feature matching, and deep learning methods like AlexNet and YOLO. Dive into object tracking techniques using Camshift, spatiotemporal context, and deep learning approaches. Apply these concepts through practical applications in artillery dynamic stability testing and multi-sensor fusion for intelligent environmental perception. Each chapter includes practice exercises to reinforce learning, culminating in a final examination to assess mastery of the material.

Syllabus

  • 第一章 图像采集与处理发展现状
    • 1.1 图像采集与处理发展现状01
    • 1.2 图像采集与处理发展现状02
    • 1.3 图像采集与处理发展现状03
    • 1.4 习题
  • 第二章 图像处理系统
    • 2.1 摄像机-图像传感器
    • 2.2 摄像机-镜头
    • 2.3 图像采集与处理系统
    • 2.4 习题
  • 第三章 图像预处理
    • 3.1 图像采集存储与灰度化
    • 3.2 图像增强
    • 3.3 边缘检测
    • 3.4 图像滤波(均值、中值、边窗滤波)
    • 3.5 图像滤波(形态学滤波)
    • 3.6 图像校正
    • 3.7 单目摄像机标定
    • 3.8 双目摄像机标定
    • 3.9 习题
  • 第四章 目标检测
    • 4.1 简单背景目标检测-阈值分割
    • 4.2 简单背景目标检测-运动信息
    • 4.3 简单背景目标检测-光流法
    • 4.4 基于特征匹配的目标检测-特征提取
    • 4.5 基于特征匹配的目标检测-特征匹配
    • 4.6 基于特征点匹配的目标检测-SIFT
    • 4.7 基于特征点匹配的目标检测-Surf
    • 4.8 基于特征点匹配的目标检测-ORB&BRISK
    • 4.9 基于特征点匹配的目标检测-关键点匹配
    • 4.10 基于AlexNet目标检测-网络模型
    • 4.11 基于AlexNet目标检测-训练过程
    • 4.12 基于yolo的目标检测
    • 4.13 习题
  • 第五章 目标跟踪
    • 5.1 基于Camshift的目标跟踪
    • 5.2 基于时空上下文的目标跟踪
    • 5.3 基于深度学习的目标跟踪
    • 5.4 习题
  • 第六章 图像目标检测技术应用
    • 6.1 火炮动态稳定精度测试
    • 6.2 多传感器融合的智能环境感知
    • 6.3 习题
  • 期末考试

    Taught by

    LI JING and WANG JUN ZHENG

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