gabor 滤波的c++实现与该类得使用简介

下载cvgabor.cpp和cvgabor.h到你的C/C++工程目录下

注：在我的资源中有改进过的cvgabor类

    相关链接为：http://download.csdn.net/source/490114

特别注意：使用该类需要opencv库的支持，如何配置环境参见：http://www.opencv.org.cn/index.php/Template:Install

它有如下的功能：

生成特定方向和尺度的gabor

生成可以显示或者保存的gabor核的实部，虚部

图像的实部，虚部或者主要（Magnitude）响应

响应可以保存在XML文件中

范例
首先包含头文件

#include "cvgabor.h"  

#include "cvgabor.h"
创建一个方向是PI/4而尺度是3的gabor

double Sigma = 2*PI;  
double F = sqrt(2.0);  
CvGabor *gabor1 = new CvGabor;  
gabor1->Init(PI/4, 3, Sigma, F); 

double Sigma = 2*PI;
double F = sqrt(2.0);
CvGabor *gabor1 = new CvGabor;
gabor1->Init(PI/4, 3, Sigma, F);

获得实部并显示它
IplImage *kernel = cvCreateImage( cvSize(gabor1->get_mask_width(), gabor1->get_mask_width()), IPL_DEPTH_8U, 1);  
kernel = gabor1->get_image(CV_GABOR_REAL);  
cvNamedWindow("Gabor Kernel", 1);  
cvShowImage("Gabor Kernel", kernel);  
cvWaitKey(0); 

IplImage *kernel = cvCreateImage( cvSize(gabor1->get_mask_width(), gabor1->get_mask_width()), IPL_DEPTH_8U, 1);
kernel = gabor1->get_image(CV_GABOR_REAL);
cvNamedWindow("Gabor Kernel", 1);
cvShowImage("Gabor Kernel", kernel);
cvWaitKey(0);

 

 

载入一个图像并显示
IplImage *img = cvLoadImage( "/local/FaceDB/CMU/rotated/217.jpg", CV_LOAD_IMAGE_GRAYSCALE );  
cvNamedWindow("Original Image", 1);  
cvShowImage("Original Image", img);  
cvWaitKey(0); 

IplImage *img = cvLoadImage( "/local/FaceDB/CMU/rotated/217.jpg", CV_LOAD_IMAGE_GRAYSCALE );
cvNamedWindow("Original Image", 1);
cvShowImage("Original Image", img);
cvWaitKey(0);

 

获取载入图像的gabor滤波响应的实部并且显示
IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);  
gabor1->conv_img(img, reimg, CV_GABOR_REAL);  
cvNamedWindow("Real Response", 1);  
cvShowImage("Real Response",reimg);  
cvWaitKey(0);  
cvDestroyWindow("Real Response"); 

IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);
gabor1->conv_img(img, reimg, CV_GABOR_REAL);
cvNamedWindow("Real Response", 1);
cvShowImage("Real Response",reimg);
cvWaitKey(0);
cvDestroyWindow("Real Response");

获取载入图像的gabor滤波响应的实部并且显示
IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);  
gabor1->conv_img(img, reimg, CV_GABOR_IMAG);  
cvNamedWindow("Imaginary Response", 1);  
cvShowImage("Imaginary Response",reimg);  
cvWaitKey(0);  
cvDestroyWindow("Imaginary Response"); 

IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);
gabor1->conv_img(img, reimg, CV_GABOR_IMAG);
cvNamedWindow("Imaginary Response", 1);
cvShowImage("Imaginary Response",reimg);
cvWaitKey(0);
cvDestroyWindow("Imaginary Response");

获取载入图像的gabor滤波响应的模并且显示
IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);  
gabor1->conv_img(img, reimg, CV_GABOR_MAG);  
cvNamedWindow("Magnitude Response", 1);  
cvShowImage("Magnitude Response",reimg);  
cvWaitKey(0);  
cvDestroyWindow("Magnitude Response"); 

IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_8U, 1);
gabor1->conv_img(img, reimg, CV_GABOR_MAG);
cvNamedWindow("Magnitude Response", 1);
cvShowImage("Magnitude Response",reimg);
cvWaitKey(0);
cvDestroyWindow("Magnitude Response");

 

这个响应可以被取样为8位的灰度图。如果你要原始的浮点类型的数据，你可以这样做

view plaincopy to clipboardprint?
IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_32F, 1);  
gabor1->conv_img(img, reimg, CV_GABOR_MAG); 

IplImage *reimg = cvCreateImage(cvSize(img->width,img->height), IPL_DEPTH_32F, 1);
gabor1->conv_img(img, reimg, CV_GABOR_MAG);

然而，这些浮点数据是不能够以上面灰度图的形式简单的显示，但是它可以被保存在一个XML文件中。

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cvSave( "reimg.xml", (IplImage*)reimg, NULL, NULL, cvAttrList(0,0)); 

本文来自CSDN博客，转载请标明出处：http://blog.csdn.net/yao_zhuang/archive/2008/06/10/2532279.aspx