MATLA

本代码主要是基于HSV的阴影检测及消除，分别提取前景及背景图像，进行色彩空间转换。HSV空间类似人类感觉色彩的方式，可以更加准确地识别阴影，并保持在计算上简单。(This code is mainly based on the HSV shadow detection and elimination, extract the foreground and the background image, respectively, for color space conversion. HSV space is similar to the ways the human feel color, can more accurately identify the shadow, and keep it simple in calculation. )

PCA、LDA人脸检测，压缩包里实现了PCA、LDA、最小距离分类器，人脸检测！(PCA, LDA face detection, compression bag to achieve the PCA, LDA, minimum distance classifier, face detection!)

说明：  锐化图片 拉普拉斯算法 两种方法 一种是自己写的一种是用了matlab里面自带的函数(ruihua picture Laplace there are two mechof a fi [as fs aflasl;nvb)

小球沿斜线运动,可以扩展到其他程序中，第一次上传，谢谢。(a ball along with a line.)

说明：  车道线检测，对道路的车道线进行检测，检测道路线(Lane line detection, detect the lane line of the road, detect the road line and extract it)

说明：  包含主要的相位恢复算法，用于解决相位恢复问题，在计算光学成像领域被广泛使用。(This code includes conventional phase retrieval algorithms designed for phase retrieval problems, which is widely used in computational optical imaging.)

在C语言下成功实现读取并显示bmp格式的图像。(Successfully read and display BMP format images in C language.)

用SAV函数实现分析图像数据的实用程序，功能上基本可以实现的。(with HBV Function analysis of image data of practical procedures, the basic function can be realized.)

水平集(level set)的基本思想是将界面看成高一维空间中某一函数ψ（称为水平集函数）的零水平集，同时界面的演化也扩充到高一维的空间中。我们将水平集函数按照它所满足的发展方程进行演化或迭代，由于水平集函数不断进行演化，所以对应的零水平集也在不断变化，当水平集演化趋于平稳时，演化停止，得到界面形状。(The level set (level set) the basic idea is to interface as a higher dimensional space in a function (called a level set function) of the zero level set, and the interface evolution also extended to higher dimensional space. We evolve or iterate the level set function according to the evolution equation it satisfies. Because the level set function keeps evolving, so the corresponding zero level set is also changing. When the level set evolves to a stable state, the evolution stops, and the interface shape is obtained.)

根据Dalal提出的HOG特征算法编写，代码简单，注释清楚，根据所处理图像的名称路径修改后可生成36*105的特征向量。(The algorithm proposed by Dalal HOG feature writing code simple, clear annotation feature vector can generate 36* 105, modified according to the name of the image processing path.)