点聚图。二维坐标，范围自动调整。

CList类的应用，有很多技巧-CList category of applications, there are many skills

在图像显示预处理中，常用到腐蚀算法，将图像进行扫描，复试后将得到灰度图。-Pretreatment of the image display, commonly used to corrosion algorithm, the image is scanned, re-testing will be grayscale.

Windows图形编程源代码 ，这本书讲的比较全面，内容也很详实-Windows graphical programming source code, this book talked about a more comprehensive and its contents are very informative

用网格实现等值线生成，并且可以对等值线线条颜色自行设定。-With grid realize isogram generation, and can contour lines of their own color settings.

一个更为复杂的2D Game实例.比之前传的复杂. Windows平台的2D Game实例2, 使用了C++和OpenGL.这个souce不但是OpenGL技术,还可以学习到两个方面的技术: part1: win32的消息循环, OpenGL的设置.画一些简单的图形. part2: 处理并且显示卡通图片.-This source focuses on 2D game development with C++ and OpenGL for Windows platform. We will not only focus on OpenGL but also talk about the designs that are commonly used in game programming with a full object oriented approach. This source include two articles: Part 1: covers the win32 message loop, the window creation and the setting-up of OpenGL. You will also learn how to draw some simple shapes. Part 2 : Covers resources handling and displaying simple animations. Contents

关于图形学中的Bresenham画线算法，中点画圆算法的实现，以及五边形，六边形，七边形填充。-graphics on the Bresenham line drawing algorithm, the midpoint of the algorithm to achieve Circle, and pentagons, hexagons, heptagon filled.

Hilditch细化算法 功能：对图象进行细化 参数：image：代表图象的一维数组 lx：图象宽度 ly：图象高度-Hilditch thinning algorithm functions : Refinement of image parameters : image : the image of the one-dimensional array lx : Image width ly : image height

目前该手写体识别系统主要分为 预处理模块： 主要包括训练数据和识别数据的读取，归一化，二值化 特征提取模块：主要包括笔划方向特征和网格密度特征，还可以根据对识别率的要求继续增加其他特征 识别（分类器）模块：主要包括SVM方法和BP神经网络的方法，其中SVM方法的识别率较高，SVM＋网格密度特征， 在小字符集情况下，达到了识别率97％以上 采用OO思想编写，适合做二次开发-currently the handwriting recognition system consists of pretreatment modules : including training data and identification data read, in one, two values of feature extraction module : the main characteristics of the direction including strokes and grid density characteristics, but also based on the identification of the requirements to continue to increase other identification ( Categories) modules : include SVM methods and BP networks, which SVM method for the identification of high SVM+ mesh density characteristics, in a small set of characters to achieve a recognition rate of over 97% using OO ideological preparation, suitable for secondary development

如何分批的投入顶点达到渲染优化目的,这个是简单的例子,可以按照需要进一步优化-How to input vertex batches to achieve the purpose of rendering optimization, this is a simple example, in accordance with the need to further optimize