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pattern-recognition
- 张学功教授的《模式识别》一书，很好的讲述了模式识别的基础知识以及应用-" Learning OpenCv" is to learn how to use the open source library for image processing OpenCv a very good basis for tutorial
LearningOpenCV_Code
- 《学习opencv》这本书的相应章节的源码，由于是1.0的版本，里面的代码都不是用C++实现的，而是用的类。只能作为入门，与类有关的还是还是上网看一些新鲜的吧~-Learning opencv " source of the corresponding chapter of this book, because it is version 1.0, code inside is not C++ achieve, but with class. Only as an entry with
LearningOpenCV_Code
- 于仕琪老师《学习opencv》一书中所有代码全解。- Learning opencv a book full solution of all the code Shiqi YU Abstract teacher.
learning-opencv
- 本代码是毛星云所编的《opencv3编程入门》的源码，是基于最新opencv3.0的，可以在vs2013上配套使用，涵盖了基本库函数的使用，共用十章例程，是一个不错的入门资料。-This code is compiled by 毛星云 " opencv3 programming entry," the source, based on the latest opencv3.0 can be supporting the use of the vs2013, covering t
LearningOpenCV_Code
- 这是《学习OpenCV》这本书的源码。作 者（美）布拉德斯基（Bradski，G.），（美）克勒（Kaehler，A.） 著，于仕琪，刘瑞祯 译-This is source code of the book <Learning OpenCV>. Author:G., Bradski, Kaehler, A., Yu Shiqi, Liu Ruizhen.
stereo_3d
- 该程序为是应用c++编程语言，基于opencv 编写的标定程序，是根据于仕琪所译的《学习opencv》中的程序该编的，在用于过程中必需要配置好opencv-The program is the application of c++ programming language, based on the opencv prepared by the calibration procedures, according to the translation of the learning opencv
exercise5-1
- QT加opencv的开发环境.实现《学习opencv》一书的练习题5-1的源码-QT plus opencv development environment. Achieve " learning opencv" a source book of exercises 5-1
LearningOpenCV_Code
- 《学习opencv》随书的源代码，非常有学习价值，给正在学习此书的朋友。- Learning opencv with the book s source code, very valuable learning, is learning the book to a friend.
LearningOpenCV_Code
- 本程序为外国名著《学习opencv》源代码，本书配套的源代码友丰富的注释，能方便广大初学者学习opencv。-This program is a foreign masterpiece learning opencv source code, the book supporting the source code rich friends notes, to facilitate the majority of beginners to learn opencv.
OpenCV_By_Example(中文版)
- 该资料中包含了《OpenCV By Example》中文版以及例程程序，该书的目录如下所示： 第1章 OpenCV的探险之旅; 第2章 OpenCV基础知识介绍; 第3章 图形用户界面和基本滤波; 第4章 深入研究直方图和滤波器; 第5章 自动光学检测、目标分割和检测; 第6章 学习目标分类; 第7章 识别人脸部分并覆盖面具; 第8章 视频监控、背景建模和形态学操作; 第9章 学习对象跟踪; 第10章 文本识别中的分割算法; 第11章 使用Tessera