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图像分割，二维图像分割，ostu算法，阈值分割(Segmentation, two-dimensional image segmentation, ostu algorithm, thresholding)

自适应模板更新的粒子滤波实时跟踪算法_赖作镁.zip(Adaptive template updating particle filter for real-time tracking algorithm _ Ryan magnesium. Zip)

图片采用3x3均值滤波，用Verilog语言描述，输入输出分别使用外同步(Pictures are filtered with 3x3 mean and described in Verilog language. Input and output are synchronized with each other.)

hough变换提取椭圆,可以从二值图像中提取出椭圆(The ellipse can be extracted from Hough transform, and ellipse can be extracted from the two valued image.)

用于图像处理中的感兴趣区域的提取，以便对物体进行识别(extract the ROI in image process)

本程序为图像锐化的经典程序，源码里有详细的标注。(the procedures for sharpening images of the classic procedures are detailed source of tagging.)

本人自己实现的单纯meanshift跟踪算法.按原理编译,适合初学者参考(I own a simple realization of the tracking algorithm meanshift. In accordance with the principle of the compiler, suitable for beginners reference)

说明：  图像处理所涉及的256转灰度，二值化等等，每个部分都是独立可执行的工程文件，很方面的代码复用(256 involved in image processing turn gray, binary, etc., are independent of each part of the project executable file, it' s code reuse)

常用的图像去噪算法，基于隐马尔可夫树模型的小波去噪 基于尺度空间和context模型相结合的自适应小波去噪 基于尺度和空间混合模型的小波图像去噪 Bayes估计阈值软门限去噪 (The denoising algorithm used in image denoising, wavelet hidden Markov tree model based on adaptive wavelet denoising combining the scale space and context model based on wavelet denoising image scale and spatial mixed model based on Bayes estimation soft threshold denoising )

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)