fast_dt

多尺度快速角点检测算法（FAST).Adaptive and generic corner detection based on the accelerated segment test. 出处 Computer Vision–ECCV 2010(Multi-scale fast corner detection algorithm (FAST) Adaptive and generic corner detection based on the accelerated segment test. Computer Vision-ECCV 2010)

本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)

图像的逆滤波 维纳滤波 同时可以对图像进行模糊处理比如运动模糊 卷积模糊(Using C++ to complete images of conversion, processing and compression process, is to learn good reference digital image processing program!)

Graph Cutshi是最近在计算机视觉中研究和应用比较多的优化算法，典型的用于stereo matching, image restortion, texture synthesis等应用，以上代码给出了graph cut，mean shift, 以及相关的ppm/pgm图像借口，本来是用于stereo matching的，已经把相关的matching的实现代码给去掉了。大家可以以此为平台做一些相关的研究和应用。 (Graph Cutshi recently in computer vision research and application of a relatively large number of optimization algorithms, typical for the stereo matching, image restortion, texture synthesis applications, the above code gives the graph cut, mean shift, and the associated ppm/pgm images an excuse, it is used for stereo matching, and has been related to matching the code to realize removed. U.S. can also be used as a platform to do some related research and applications.)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)

说明：  一个用VC++6.0编的程序例子，实现远程屏幕图像的传输 (a VC 6.0 Provision procedures example, remote screen image transmission)

VisualC++数字图像处理技术详解第2版光盘-第七章(VisualC++ digital image processing technology Detailed Version 2 CD- Chapter VII)

边缘检测与提取，轮廓跟踪 注意事项： 运行时，文件c: est.bmp必须存在(Edge detection and extraction, contour tracing Note: run-time, file c: test.bmp must exist)

针对万工显螺旋显微镜视场图像特点，编写了Matlab 语言的图像处理算法用于万工显自动读数( The program which is developed by MATLAB language can be used for auto-reading of universal tools microscope measurement result)

图像拼接小程序，使用直接对比的方法进行拼接并用加权平均的方法进行融合 (a simple program for image splicing )