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OpenCV图像内轮廓填-孔洞填充

2016-04-09 00:00 459 查看
摘要: 图像内轮廓填充通常称为孔洞填充,主要用于目标提取。

//test
#include "stdafx.h"
#include "cxcore.h"
#include "cv.h"
#include "highgui.h"

// 内轮廓填充
// 参数:
// 1. pBinary: 输入二值图像,单通道,位深IPL_DEPTH_8U。
// 2. dAreaThre: 面积阈值,当内轮廓面积小于等于dAreaThre时,进行填充。
void FillInternalContours(IplImage *pBinary, double dAreaThre)
{
double dConArea;
CvSeq *pContour = NULL;
CvSeq *pConInner = NULL;
CvMemStorage *pStorage = NULL;
// 执行条件
if (pBinary)
{
// 查找所有轮廓
pStorage = cvCreateMemStorage(0);
cvFindContours(pBinary, pStorage, &pContour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
// 填充所有轮廓
cvDrawContours(pBinary, pContour, CV_RGB(255, 255, 255), CV_RGB(255, 255, 255), 2, CV_FILLED, 8, cvPoint(0, 0));
// 外轮廓循环
int wai = 0;
int nei = 0;
for (; pContour != NULL; pContour = pContour->h_next)
{
wai++;
// 内轮廓循环
for (pConInner = pContour->v_next; pConInner != NULL; pConInner = pConInner->h_next)
{
nei++;
// 内轮廓面积
dConArea = fabs(cvContourArea(pConInner, CV_WHOLE_SEQ));
printf("%f\n", dConArea);
if (dConArea <= dAreaThre)
{
cvDrawContours(pBinary, pConInner, CV_RGB(255, 255, 255), CV_RGB(255, 255, 255), 0, CV_FILLED, 8, cvPoint(0, 0));
}
}
}
printf("wai = %d, nei = %d", wai, nei);
cvReleaseMemStorage(&pStorage);
pStorage = NULL;
}
}
int Otsu(IplImage* src)
{
int height=src->height;
int width=src->width;
//histogram
float histogram[256] = {0};
for(int i=0; i < height; i++)
{
unsigned char* p=(unsigned char*)src->imageData + src->widthStep * i;
for(int j = 0; j < width; j++)
{
histogram[*p++]++;
}
}
//normalize histogram
int size = height * width;
for(int i = 0; i < 256; i++)
{
histogram[i] = histogram[i] / size;
}
//average pixel value
float avgValue=0;
for(int i=0; i < 256; i++)
{
avgValue += i * histogram[i];  //整幅图像的平均灰度
}
int threshold;
float maxVariance=0;
float w = 0, u = 0;
for(int i = 0; i < 256; i++)
{
w += histogram[i];  //假设当前灰度i为阈值, 0~i 灰度的像素(假设像素值在此范围的像素叫做前景像素) 所占整幅图像的比例
u += i * histogram[i];  // 灰度i 之前的像素(0~i)的平均灰度值: 前景像素的平均灰度值
float t = avgValue * w - u;
float variance = t * t / (w * (1 - w) );
if(variance > maxVariance)
{
maxVariance = variance;
threshold = i;
}
}
return threshold;
}
int main()
{
IplImage *img = cvLoadImage("c://temp.jpg", 0);
IplImage *bin = cvCreateImage(cvGetSize(img), 8, 1);
int thresh = Otsu(img);
cvThreshold(img, bin, thresh, 255, CV_THRESH_BINARY);
FillInternalContours(bin, 200);
cvNamedWindow("img");
cvShowImage("img", img);
cvNamedWindow("result");
cvShowImage("result", bin);
cvWaitKey(-1);
cvReleaseImage(&img);
cvReleaseImage(&bin);
return 0;
}
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