我在 Visual Studio 2010 上使用 opencv2.2。我编写了一个代码来预处理 OCR 的图像。我正在使用很多轨迹栏来改变参数。预处理功能之一是通过绘制轮廓并根据大小将它们过滤掉来去除小斑点。但是,当我运行程序时,cvDrawContours 函数给了我一个错误。基本上我会弹出一个错误,说 R6010 -abort 已被调用。命令行说在第 641 行的 matrix.cpp 中有一个未知的数组类型。我在这里包含我的代码。该问题由 BlobFunc 函数中的 cvDrawContours 函数调用。
#include <C:\OpenCV2.2\modules\core\include\opencv2\core\core.hpp>
#include <C:\OpenCV2.2\modules\highgui\include\opencv2\highgui\highgui.hpp>
#include <iostream>
#include <string.h>
#include <C:\OpenCV2.2\include\opencv\cv.h>
#include <stdlib.h>
#include <C:\OpenCV2.2\modules\highgui\include\opencv2\highgui\highgui_c.h>
#include <C:\Users\Administrator\Documents\blobs\blob.h>
#include <C:\Users\Administrator\Documents\blobs\BlobResult.h>
using namespace cv;
using namespace std;
int MAX_KERNEL_LENGTH = 30;
int counter=0;
int Blurtype=0;
int Kern=5;
int *Kernp=&Kern;
int betaval=50;
int *betavalp=&betaval;
int Threshtype=0;
int Threshval=30;
int size=10;
Mat src1, src2, dst1, dst2, dst3;
CvScalar black=CV_RGB( 0, 0, 0 ); // black color
CvScalar white=CV_RGB( 255, 255, 255 ); // white color
double area;
void BlobFunc(int,void*);
int main( int argc, char** argv )
{
//Read Input
src1 = imread(argv[1]);
if( !src1.data ) { printf("Error loading src1 \n"); return -1; }
//Create Windows
namedWindow("Original Image",1);
namedWindow("Binarized Image",1);
namedWindow("Gray Image",1);
namedWindow("Sharpened Image",1);
namedWindow("Blurred Image",1);
imshow("Original Image",src1);
namedWindow("Blobs",1);
//Create Trackbars
cvtColor(src1,src2,CV_RGB2GRAY);
imshow("Gray Image",src2);
threshold( src2, dst1, Threshval, 255,Threshtype);
imshow("Binarized Image",dst1);
createTrackbar("Kernel","Blurred Image",&Kern,MAX_KERNEL_LENGTH,BlobFunc);
createTrackbar("BlurType","Blurred Image",&Blurtype,3,BlobFunc);
createTrackbar("Betaval","Sharpened Image",&betaval,100,BlobFunc);
createTrackbar("Threshold value","Binarized Image",&Threshval,255,BlobFunc);
createTrackbar("Type","Binarized Image",&Threshtype,4,BlobFunc);
createTrackbar("Size","Blobs",&size,100,BlobFunc); //Size of Blob
waitKey(0);
return 0;
}
void BlobFunc(int,void*)
{
CvMemStorage *storage=cvCreateMemStorage(0);
CvSeq *contours=0;
cvtColor(src1,src2,CV_RGB2GRAY);
imshow("Gray Image",src2);
threshold( src2, dst1, Threshval, 255,Threshtype);
imshow("Binarized Image",dst1);
for ( int i = 1; i < Kern; i = i + 2 )
{
if (Blurtype==0)
{
blur(dst1,dst2, Size( i, i ), Point(-1,-1) );
}
else if (Blurtype==1)
{
GaussianBlur( dst1, dst2, Size( i, i ), 0, 0 );
}
else if (Blurtype==2)
{
medianBlur ( dst1, dst2, i );
}
else if (Blurtype==3)
{
bilateralFilter ( dst1, dst2, i, i*2, i/2 );
}
}
imshow("Blurred Image",dst2);
addWeighted( dst1, 1, dst2, -double(betaval)/100, 0.0, dst3);
imshow("Sharpened Image",dst3);
IplImage img=dst3;
cvFindContours(&img,storage,&contours,sizeof(CvContour),CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE);
IplImage *img_out=cvCreateImage( cvGetSize(&img), 8, 3 );
cvZero( &img_out );
for( ; contours != 0; contours = contours->h_next )
{
cvDrawContours( &img_out, contours, black, black, -1, CV_FILLED, 8 );
}
Mat imgout=img_out;
cvReleaseMemStorage( &storage );
imshow("Blobs",imgout);
}