it used for color reduction in images

MS.NET GDI+平台。使用C#开发。-MS.NET GDI platform. Using C# development.

实现图像的分割迭代算法、峰谷算法、半阈值算法的vc代码-achieve iterative image segmentation algorithm, algorithm- trough, semi-threshold algorithm vc code

orl人脸数据库第4部分,因体积大,分成几个部分,做人脸的必需.-02:00 Face database Part 4, because of their size, divided into several parts, the essential human face.

把任一窗口的内容存为位图。有兴趣的下载试试看，只是个小程序。-put the contents of a window of survival for bitmap. Interested try to download, it is a small procedure.

这是一个基于对话框的计算器程序。是使用mfc编的。对初学者有一点帮助-This is a calculator source code based on dialog box with the help of mfc. It may help the beginner of VC.

视频游戏开发C 语言源程序，这是个启盟的东东呀，希望能对学C的人有很帮助-C language source code, which is the Eastern League Kai um, in hopes of learning C there was help

这是一个在对话框中显示图片的程序。可以显示24位或者是32位bmp格式的位图-This is a dialog box shown in the photo process. It shows 24 or 32 bmp format bitmaps

用来捕捉正在播放的视频文件的图像窗口内容，比如使用Media Player。这个功能使用DirectX and DirectShow可能很容易就实现了，当时我没有看到相关的文章或者源代码，据我所知，HyperSnap-DX好像是捕捉播放的视频图像的一个工具。 我做了一个示例程序，当你使用播放器播放视频文件的时候，运行这个程序，在“Option”菜单中选择“Start Caputre”即可进行捕捉，在“File”菜单可以选择“Save...”菜单可以保存捕捉的图像为bmp文件。-is used to capture video broadcast images of the document window, for example the use of Media Player. This function using DirectX and DirectShow may be very easy to achieve. At that time, I did not see the article or source code, as far as I know, HyperSnap- DX is like to catch the broadcast of a video image tools. I have done a sample procedure, when you use players to play video files, the operating procedures, "Option" menu, select "Start Caputre" of catching, in the "File" menu select "Save ..." menu can be saved as image capture bmp document.

搜索到的比较好的箭头绘画源码,vc++下,大家可参考使用-search of the relatively good source arrow painting, vc, we can use and reference

针对航空照片中自动目标识别的复杂性．该文提出了一种基于神经网络的自动目标识别算法， 算法包括检测和虚警排除两个阶段．检1删阶段是在整幅区域中i挂行快速搜寻．找出所有可能的目标 虚 警排障阶段是对检测阶段得到的结果进行进一步的验证， 在尽可能保留全部真目标的前提下，将伪目标 排除．实验结果证明了算法的可行性． 关键词 神经网络，航空照片， 自动目标识别-against aerial photographs Automatic Target Recognition of complexity. This paper presents a neural network-based automatic target recognition algorithm, the algorithm including the detection and false alarm ruled out in two stages. Frederick stage is a cut in the whole region i linked to fast-track the search. To identify all possible targets false alarm remove obstacles stage of the testing phase results further verification, reservations at all possible real targets on the premise that goal will be to exclude false. Experimental results demonstrate the feasibility of the algorithm. Keywords neural network, aerial photographs, automatic target recognition