基于紋理特征的陰影抑制

原理：

該方法在實作過程中主要結合了車輛陰影的4個特性：

(1) 陰影的亮度值比背景的亮度值小；

(2) 運動陰影與背景的梯度密度差低于運動車輛與背景的梯度密度差；

(3) 陰影在車輛的周圍區域，即可以在車輛外部的任意方向，但不在車輛

内部區域；

(4) 陰影的邊緣像素比車輛的邊緣像素少。

代碼：

"main.h"

#include "highgui.h"

#include "cv.h"

#include "cxcore.h"

#include <math.h>

#define TEMPLATEM 3

#define TEMPLATEN 3

"main,cpp"

#include "main.h"

int main(int argc,int **argv)

{

 IplImage *img =cvLoadImage("F:\\testData\\test.BMP");

 IplImage *gray=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *backgray=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *binedge=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

  IplImage *differgray=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

  IplImage *edgegray=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_16S,1);

 IplImage *kernel1=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *kernel2=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *kernel3=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *kernel4=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 IplImage *bindetect=cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);

 float a[25]={0,0,0,0,0,0,0,0,0,0,1,1,-4,1,1,0,0,0,0,0,0,0,0,0,0};

 float b[25]={0,0,1,0,0,0,0,1,0,0,0,0,-4,0,0,0,0,1,0,0,0,0,1,0,0};

 float c[25]={0,0,0,0,1,0,0,0,1,0,0,0,-4,0,0,0,1,0,0,0,1,0,0,0,0};

 float d[25]={1,0,0,0,0,0,1,0,0,0,0,0,-4,0,0,0,0,0,1,0,0,0,0,0,1};

 CvMat kernelA=cvMat(5,5,CV_32F,a);

 CvMat kernelB=cvMat(5,5,CV_32F,b);

 CvMat kernelC=cvMat(5,5,CV_32F,c);

 CvMat kernelD=cvMat(5,5,CV_32F,d);

 cvCvtColor(img,gray,CV_BGR2GRAY);

 img=cvLoadImage("F:\\testData\\test1.BMP");

 cvCvtColor(img,backgray,CV_BGR2GRAY);

 cvNamedWindow("DIFFER",CV_WINDOW_AUTOSIZE);

 cvNamedWindow("GRAY",CV_WINDOW_AUTOSIZE);

 cvNamedWindow("BACKGROUD",CV_WINDOW_AUTOSIZE);

 cvNamedWindow("EDGE",CV_WINDOW_AUTOSIZE);

    cvNamedWindow("BINEDGE",CV_WINDOW_AUTOSIZE);

 cvAbsDiff(gray,backgray,differgray);

 cvThreshold(differgray,bindetect,20,255,CV_THRESH_BINARY);

 cvSobel(differgray,edgegray,1,1,3);

  //cvCanny(differgray,binedge,150,100,3);

 cvConvertScale(edgegray, binedge, 1.0, 0.0);

 cvThreshold(binedge,binedge,50,255,CV_THRESH_BINARY);

 cvFilter2D(binedge,kernel1,&kernelA,cvPoint(-1,-1));

 cvFilter2D(binedge,kernel2,&kernelB,cvPoint(-1,-1));

 cvFilter2D(binedge,kernel3,&kernelC,cvPoint(-1,-1));

 cvFilter2D(binedge,kernel4,&kernelD,cvPoint(-1,-1));

 cvMax(kernel1,binedge,binedge);

 cvMax(kernel2,binedge,binedge);

 cvMax(kernel3,binedge,binedge);

 cvMax(kernel4,binedge,binedge);

  for (int i=0;i < gray->width;i++)

   for (int j=0;j < gray->height;j++)

   {

    if (((uchar*)(bindetect->imageData+j*bindetect->widthStep))[i]==255&&((uchar*)(differgray->imageData+j*differgray->widthStep))[i]<80)

     ((uchar*)(bindetect->imageData+j*bindetect->widthStep))[i]=((uchar*)(binedge->imageData+j*binedge->widthStep))[i];

   }

 //cvErode(bindetect, bindetect, 0, 1);//“最小化”操作，亮的區域被隔離并且縮小

 cvDilate(bindetect, bindetect, 0, 1);

 cvShowImage("BACKGROUD",bindetect);

 cvShowImage("DIFFER",differgray);

 cvShowImage("GRAY",gray);

 cvShowImage("EDGE",edgegray);

 cvShowImage("BINEDGE",binedge);

 cvWaitKey(0);

 cvReleaseImage(&backgray);

 cvReleaseImage(&gray);

 cvReleaseImage(&differgray);

 cvReleaseImage(&edgegray);

 cvDestroyWindow("GRAY");

 cvDestroyWindow("RGB");

 cvDestroyWindow("DIFFER");

 cvDestroyWindow("EDGE");

}

 效果：

與背景內插補點圖

陰影抑制二值圖

參考文獻：

《基于視覺的交通違章停車檢測方法研究》 褚洪君 哈爾濱工業大學 2009 年 6 月