MedianFilterSmooth

Keystone Transform in ground moving target detection，it s very useful new comer(Keystone Transform in ground moving target detection)

利用形态学，霍夫（Hough）变换，实现畸变QR码的4个角点的定位。(To correct the distortion of the QR code,use morphology operation, Hough transform, to locat the positioning of the four corner points)

对图像变形的一些基本算法的介绍和功能的描述等 (about marphing )

基于PCL的估算散乱点云的法矢量，并进行颜色渲染显示(estimation of normal vectors for point clouds and color rendering display based on PCL)

VisualC++数字图像处理技术详解第2版光盘-第七章(VisualC++ digital image processing technology Detailed Version 2 CD- Chapter VII)

过特定人语音情感数据库的建立；语音情感特征提取；语音情感分类器的设计，完成了一个特定人语音情感识别的初步系统。对于单个特定人，可以识别平静、悲伤、愤怒、惊讶、高兴5种情感，除愤怒和高兴之间混淆程度相对较大之外，各类之间区分特性良好，平均分类正确率为93.7 。对于三个特定人组成的特定人群，可以识别平静、愤怒、悲伤3种情感，各类之间区分特性良好，平均分类正确率为94.4 。其中分类器采用混合高斯分布模型。(The system of speech emotion recognition)

边缘检测 Edge Detection Edge Detection(Edge Detection)

用AAM算法进行人脸特征点的标定，即对人脸的眼睛，眉毛，嘴巴，鼻子及脸的轮廓进行标记，此代码标记了68个特征点。(AAM algorithm for facial feature points calibration, calibration of this code is the 68 feature points, see the instance document.)

说明：   最简单的差分格式有向前、向后和中心3种。 向前差分：f (n)=f(n+1)-f(n) 向后差分：f (n)=f(n)-f(n-1) 中心差分：f (n)=[f(n+1)-f(n-1)]/2(The easiest difference format forward, backward, and three kinds of centers. Forward differencing: f (n) = f (n+ 1)-f (n) Backward difference: f (n) = f (n)-f (n-1) Central difference: f (n) = [f (n+ 1)-f (n-1)]/2)

opencv是图像处理中常用到的工具箱，本资料为基于此工具箱的图像处理匹配算法SURF的实现代码。(opencv is commonly used in image processing to the toolbox, the toolbox based on this information for the image processing algorithm to match the achievement of SURF code.)