C Builder Image louver effects and is simple and fast operation and the results...

坐标输入对图像进行分割的行数和列数，而后对每个小块求直方图，文件输出-Coordinates input to the image segmentation of the number of rows and columns, and then seek for each histogram plots, the document output

Marr-Hildreth 边缘检测算法-Marr-Hildreth edge detection algorithm

基于盲解卷积的相位差算法，图像恢复，文件包里面有仿真和LBFGS优化算法-The phase difference based on blind deconvolution algorithm, vogel

利用EXCE里数据在AUTOCAD中找位置-Use EXCE where to find the location of data in AUTOCAD

利用OpenCV进行轮廓提取，很好用！对于初学openCv的人来说是个很好的入门例程-Use OpenCV for contour extraction, very good use! OpenCv for the beginner who is a good entry-routine

使用说明 使用时打开此例题目录下pic中的图片，然后依次单击按钮“转”、“1”、“2”、“3”、“4”和“5”，就可以实现精确的车牌定位。 具体步骤 1.24位真彩色->256色灰度图。 2.预处理:中值滤波。 3.二值化:用一个初始阈值T对图像A进行二值化得到二值化图像B。 初始阈值T的确定方法是:选择阈值T=Gmax-(Gmax-Gmin)/3,Gmax和Gmin分别是最高、最低灰度值。 该阈值对不同牌照有一定的适应性,能够保证背景基本被置为0,以突出牌照区域。 4.削弱背景干扰。对图像B做简单的相邻像素灰度值相减,得到新的图像G,即Gi,j=|Pi,j-Pi,j-1|i=0,1,…,439 j=0,1,…,639Gi,0=Pi,0,左边缘直接赋值,不会影响整体效果。 5.用自定义模板进行中值滤波 区域灰度基本被赋值为0。考虑到文字是由许多短竖线组成,而背景噪声有一大部分是孤立噪声,用模板(1,1,1,1,1)T对G进行中值滤波,能够得到除掉了大部分干扰的图像C。 6.牌照搜索:利用水平投影法检测车牌水平位置,利用垂直投影法检测车牌垂直位置。 7.区域裁剪,截取车牌图像。-my english is poor

The aim of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extraction, and classification. This program use Image Processing Toolbox to get it. For more information, visit: http://www.matpic.com

mblur filter for image in c .Implementation

简单图形学，提供投影算法-simple graphics, providing projection algorithm

中科院的多视角人脸识别 Real-Time Multi-View Face Detection-Chinese Academy of Sciences of the Multi-View Face Recognition Real-Time Multi-View Face Detection