利用K均值聚类的方法实现人体的检测，混合高斯模型建立背景并实时更新...

opencv基础配套光盘代码，3-1，与大家分享，我会继续上传-based on CD-ROM package opencv code ,3-1 to share with you, I will continue to upload

均值滤波对高斯噪声的效果 二维自适应维纳滤波对高斯噪声的滤除效果 对加入椒盐噪声的图像分别作均值、中值和维纳滤波 分别使用二维统计滤波对椒盐噪声和高斯噪声进行滤波 利用wrcoef2函数进行图像去噪-Mean filter on the effect of Gaussian noise two-dimensional Adaptive Wiener filtering of the Gaussian noise filtering effect the image to join Salt and pepper noise, respectively for the mean, median and Wiener filtering respectively, using two-dimensional statistical filtering of the Salt & Pepper noise and Gaussian noise filter the use of image denoising wrcoef2 function

来自于VC++数字图像处理典型算法及其实现这本书，对于初学者有很大的帮助。-very usrful,from a classical book

模式识别的一些预处理知识源程序，初学者在编制程序时可以参考- Two programs are included in this directory: STK2RAS takes a stroke file as input and converts it into a bit-per-pixel representation (along with some header information, see RASHEADR.H). The output of the STK2RAS program is a .RAS file. The GRID1 program found in this directory is a PM program which takes a .RAS file as input and displays the image. Notice that the GRID1 program uses run length compression. See class RLCX to scale the image.

一个目标检测识别的matlab程序，用于初学者使用matlab编程，用的比校全面-Identification of a target detection matlab program for beginners to use matlab to program than the school used a comprehensive

使用DELPHI 编写的实现三角形 以及可以推广到多边形窗体 自己参考源码 进行修改-prepared to use Delphi as well as the realization of triangular polygons can be promoted to Form reference to source code changes

采用国际标准测试图cameraman进行测试。分别采用均匀性度量法、类间最大距离法、最大熵方法三种方法进行图像分割。并附有注释、程序清晰、易于阅读。相信图像初学者阅读后应该有很大的收益。-junyunxingduliangfa, leijianzuidajulifa, zuidashangfangfa,

直方图均衡化（图形的翻转、拉伸、变形等操作）-histogram equalization (graphics overturned, tensile deformation etc)

HARRIS算法角点检测源程序，目前应用广泛且效果最好的。-HARRIS source corner detection algorithm is currently widely used and best.

sltoolbox (Statistical Learning Toolbox) organizes a comprehensive set of matlab codes in statistical learning, pattern recognition and computer vision. It includes 256 m-files in 24 categories, which are from low-level computational routines to high-level frameworks and algorithms