标签:++ point statistic htm ali ntb 一个 提取 利用
採用OpenCV249利用边缘检測、轮廓检測、腐蚀实现的车牌定位,详细为:
Mat srcImage=imread("image/000.jpg");
//imshow("a",srcImage);
int i,j;
int cPointR,cPointG,cPointB,cPoint;//currentPoint;
Mat resizeImage;
resize(srcImage,resizeImage,Size(400,300));
Mat grayImage;
cvtColor(resizeImage,grayImage, CV_BGR2GRAY);
Mat medianImage;
medianBlur(grayImage,medianImage,3); //最后一个參数须要为奇数
Mat sobelImage;
//參数为:源图像。结果图像,图像深度,x方向阶数。y方向阶数。核的大小。尺度因子,添加的值
Sobel(medianImage,sobelImage,CV_8U,1,0,3,0.4,128);
Mat normalizeImage;
normalize(sobelImage,normalizeImage,255,0,CV_MINMAX);
Mat binaryImage;
threshold(normalizeImage,binaryImage, 100, 255, THRESH_BINARY_INV );
Mat closeImage;
//morphologyEx(binaryImage,closeImage,MORPH_CLOSE,Mat(3,1,CV_8U),Point(0,0),10); //闭运算
Mat openImage(closeImage.rows,closeImage.cols,CV_8UC1);
//morphologyEx(closeImage,openImage,MORPH_OPEN,Mat(3,3,CV_8U),Point(0,0),1); //开运算
// erode(openImage,openImage,Mat(3,3,CV_8U),Point(-1,-1),10);
dilate(binaryImage,openImage,Mat(3,3,CV_8U),Point(-1,-1),6);
/*
Mat rgbImage;
cvtColor(openImage,rgbImage, CV_GRAY2BGR);
*/
//cvtColor(openImage,openImage, CV_BGR2GRAY);
//vector<vector<Point> > contours;
//vector<Vec4i> hierarchy;
//openImage=imread("test.png");
imshow("openImage",openImage);
/// Detect edges using canny
// Canny( src_gray, canny_output, thresh, thresh*2, 3 );
/// Find contours
/* Mat thresholdImage;
cvtColor(openImage,openImage, CV_BGR2GRAY);
threshold( openImage,thresholdImage,127, 255, THRESH_BINARY );
openImage=thresholdImage;*/
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours(openImage, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
for( int i = 0; i < contours.size(); i++ )
{
//使用边界框的方式
CvRect aRect = boundingRect(contours[i]);
int tmparea=aRect.height*aRect.height;
if (((double)aRect.width/(double)aRect.height>2)&& ((double)aRect.width/(double)aRect.height<6)&& tmparea>=200&&tmparea<=25000)
{
rectangle(resizeImage,cvPoint(aRect.x,aRect.y),cvPoint(aRect.x+aRect.width ,aRect.y+aRect.height),color,2);
//cvDrawContours( dst, contours, color, color, -1, 1, 8 );
}
}
imshow("contour",resizeImage);
測试了非常多图片。这几张基本有个样子。通过调整腐蚀的次数。能够针对不同的图像进行定位。
參考资料:
学习OpenCV——车牌检測(定位):http://blog.csdn.net/yangtrees/article/details/7444470
标签:++ point statistic htm ali ntb 一个 提取 利用
原文地址:https://www.cnblogs.com/ldxsuanfa/p/10013814.html