该压缩包里面含有labview vision检测的多个例子。非常适合新手学习，对视觉检测的原理又给好的理解。

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Computer Vision,A Modern Approach(中文版) 计算机视觉的现代方法！

Table of Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1. Basic Image Handling and Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 PIL—The Python Imaging Library 1 1.2 Matplotlib 3 1.3 NumPy 7 1.4 SciPy 16 1.5 Advanced Example: Image De-Noising 23 Exercises 26 Conventions for the Code Examples 27 2. Local Image Descriptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.1 Harris Corner Detector 29 2.2 SIFT—Scale-Invariant Feature Transform 36 2.3 Matching Geotagged Images 44 Exercises 51 3. Image to Image Mappings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1 Homographies 53 3.2 Warping Images 57 3.3 Creating Panoramas 70 Exercises 77 4. Camera Models and Augmented Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.1 The Pin-Hole Camera Model 79 4.2 Camera Calibration 84 4.3 Pose Estimation from Planes and Markers 86 4.4 Augmented Reality 89 Exercises 98 iii 5. Multiple View Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.1 Epipolar Geometry 99 5.2 Computing with Cameras and 3D Structure 107 5.3 Multiple View Reconstruction 113 5.4 Stereo Images 120 Exercises 125 6. Clustering Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 6.1 K-Means Clustering 127 6.2 Hierarchical Clustering 133 6.3 Spectral Clustering 140 Exercises 145 7. Searching Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 7.1 Content-Based Image Retrieval 147 7.2 VisualWords 148 7.3 Indexing Images 151 7.4 Searching the Database for Images 155 7.5 Ranking Results Using Geometry 160 7.6 Building Demos andWeb Applications 162 Exercises 165 8. Classifying Image Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 8.1 K-Nearest Nei

A Guide to Convolutional Neural Networks for Computer Vision-Morgan & Claypool(2018).pdf

基本包括了所有出现于各种数字图像处理教材、论文的标准测试图片，共335张，classic，oldclassic，aerials，misc，sequences，textures，Kodak，special，additional，Public-Domain Test Images for Homeworks and Projects，Photos with lines & edges，Bright colours photos……

原书电子版，非扫描

Halcon是世界顶级的机器视觉软件，halcon 10 在三维上比以前的版本有了很大改进，希望对各位做三维视觉的朋友能有帮助！

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