imagetest12

用matlab基本语句实现直方图均衡化库函数histeq的功能(matlab histeq)

基于MATLAB的数字图像处理程序，给出一幅染色体图像，通过边缘检测，及腐蚀等算法统计出染色体的数量。(MATLAB-based digital image processing procedures, are given a piece of chromosome images, through the edge detection, and corrosion, such as algorithm statistics the number of chromosomes.)

读取图像，转化为二值，去除毛刺噪点像素，去除孤立的前景像素，膨胀，对颗粒进行计数(particle count，)

基于dwt的数字图像水印技术的matlab源代码。包括嵌入和提取，效果不错。(Dwt-based digital image watermarking technique matlab source code. Including the embedding and extraction, good results.)

k-均值聚类法用于各种图像的聚类、分割问题，希望可以对您有利(k-means clustering method for a variety of image clustering, segmentation)

Viola-Jones 算法的人脸检测程序，附带检测图片(for detection using Viola-Jones Algorithm. To save Cropped Picture you need to change the folder location.)

织物疵点检测和识别系统.采用2中方法，有gui界面，支持实际纺织物的检测(Fabric defect detection and identification systems. Using 2 methods, gui interface, support for the detection of the actual textile)

人脸识别考勤系统

说明：  计算机图形学中应用VC++6.0和DirectX 8.0 SDK制作彩色旋转的金字塔和正方体的小程序(computer graphics application VC 6.0 and DirectX 8.0 SDK produced color rotating cube pyramid and the small program)

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)