用hmm实现的人脸识别及其文档，转自国外网站

图像处理中常用的标准灰度图像（bmp格式），包括baboon,boat,lena,peppers等-Standard gray image-it commonly used in image processing (bmp format), including the baboon, boat, lena, peppers, etc.

本程序主要实现对图像的分割，主要方法有并行边界分割，串行边界分割，并行区域分割，串行区域分割，并实现了Canny算子-The main achievement of this process of image segmentation, the main method of parallel boundary partition, serial border segmentation, region segmentation parallel, serial region segmentation, and the realization of the Canny operator

图像修复。它可以自动恢复图像。

多边形常用算法模块 1. 判断多边形是否简单多边形2. 检查多边形顶点的凸凹性 3. 判断多边形是否凸多边形 4. 求多边形面积5. 判断多边形顶点的排列方向，方法一 6. 判断多边形顶点的排列方向，方法二 7. 射线法判断点是否在多边形内8. 判断点是否在凸多边形内-Does the polygon commonly used algorithm module 1. judgements polygons whether simple polygon. 2. inspections polygons apex convex-concave. 3. judgements polygons whether raised- polygon. 4. ask the polygon area. 5. judgements polygons apex the arrangement direction, the method 1. 6. judgements polygons apex arrangement direction, the method 2. 7. beams methods to sentence the break point whether. 8. sentences the break point in the polygon whether in raised- polygon

直方图规定化 规定灰度为[zeros(1,49),0.1,zeros(1,49),0.2,zeros(1,49),0.3,zeros(1,49),0.1,zeros(1,49),0.2,zeros(1,49),0.1] 直方图均衡化，四邻域平均法，阈值平均法 加权平均法- Gray histogram specification provides for the [zeros (1,49), 0.1, zeros (1,49), 0.2, zeros (1,49), 0.3, zeros (1,49), 0.1, zeros (1, 49), 0.2, zeros (1,49), 0.1] histogram equalization, neighbors and domain average method, the threshold average method weighted average method

find contours in image using OpenCV each contour s pixels are stored in a sequence(CvSeq)

在VC6.0中的一些基本操作,常常用来进行简单的学习和常规的练习 -in VC6.0 of some of the basic operations, often used for the study and simple conventional exercise

A set of matlab funcitons used in the field of digital image processing (pattern recognition).

image processing and affine transformation

PCA-SIFT实现图像的不变性特征提取,利用主元分析提取SIFT特征,提高了效率.-PCA-SIFT invariant image feature extraction, using principal component analysis extracted SIFT features, improved efficiency.