使用 OpenCV 进行角度和尺度不变模板匹配 [英] Angle and Scale Invariant template matching using OpenCV
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问题描述
函数将模板图像从 0 度旋转到 180 度(或最多 360 度)以搜索源图像中所有相关匹配项(所有角度)，即使比例不同.
Function rotates the template image from 0 to 180 (or upto 360) degrees to search all related matches(in all angles) in source image even with different scale.
该函数是用 OpenCV C 接口编写的.当我尝试将它移植到 openCV C++ interface 时，我遇到了很多错误.有人请帮我将它移植到 OpenCV C++ 接口.
The function had been written in OpenCV C interface. When I tried to port it to openCV C++ interface , I am getting lot of errors. Some one please help me to port it to OpenCV C++ interface.
void TemplateMatch()
{
int i, j, x, y, key;
double minVal;
char windowNameSource[] = "Original Image";
char windowNameDestination[] = "Result Image";
char windowNameCoefficientOfCorrelation[] = "Coefficient of Correlation Image";
CvPoint minLoc;
CvPoint tempLoc;
IplImage *sourceImage = cvLoadImage("template_source.jpg", CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR);
IplImage *templateImage = cvLoadImage("template.jpg", CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR);
IplImage *graySourceImage = cvCreateImage(cvGetSize(sourceImage), IPL_DEPTH_8U, 1);
IplImage *grayTemplateImage =cvCreateImage(cvGetSize(templateImage),IPL_DEPTH_8U,1);
IplImage *binarySourceImage = cvCreateImage(cvGetSize(sourceImage), IPL_DEPTH_8U, 1);
IplImage *binaryTemplateImage = cvCreateImage(cvGetSize(templateImage), IPL_DEPTH_8U, 1);
IplImage *destinationImage = cvCreateImage(cvGetSize(sourceImage), IPL_DEPTH_8U, 3);
cvCopy(sourceImage, destinationImage);
cvCvtColor(sourceImage, graySourceImage, CV_RGB2GRAY);
cvCvtColor(templateImage, grayTemplateImage, CV_RGB2GRAY);
cvThreshold(graySourceImage, binarySourceImage, 200, 255, CV_THRESH_OTSU );
cvThreshold(grayTemplateImage, binaryTemplateImage, 200, 255, CV_THRESH_OTSU);
int templateHeight = templateImage->height;
int templateWidth = templateImage->width;
float templateScale = 0.5f;
for(i = 2; i <= 3; i++)
{
int tempTemplateHeight = (int)(templateWidth * (i * templateScale));
int tempTemplateWidth = (int)(templateHeight * (i * templateScale));
IplImage *tempBinaryTemplateImage = cvCreateImage(cvSize(tempTemplateWidth, tempTemplateHeight), IPL_DEPTH_8U, 1);
// W - w + 1, H - h + 1
IplImage *result = cvCreateImage(cvSize(sourceImage->width - tempTemplateWidth + 1, sourceImage->height - tempTemplateHeight + 1), IPL_DEPTH_32F, 1);
cvResize(binaryTemplateImage, tempBinaryTemplateImage, CV_INTER_LINEAR);
float degree = 20.0f;
for(j = 0; j <= 9; j++)
{
IplImage *rotateBinaryTemplateImage = cvCreateImage(cvSize(tempBinaryTemplateImage- >width, tempBinaryTemplateImage->height), IPL_DEPTH_8U, 1);
//cvShowImage(windowNameSource, tempBinaryTemplateImage);
//cvWaitKey(0);
for(y = 0; y < tempTemplateHeight; y++)
{
for(x = 0; x < tempTemplateWidth; x++)
{
rotateBinaryTemplateImage->imageData[y * tempTemplateWidth + x] = 255;
}
}
for(y = 0; y < tempTemplateHeight; y++)
{
for(x = 0; x < tempTemplateWidth; x++)
{
float radian = (float)j * degree * CV_PI / 180.0f;
int scale = y * tempTemplateWidth + x;
int rotateY = - sin(radian) * ((float)x - (float)tempTemplateWidth / 2.0f) + cos(radian) * ((float)y - (float)tempTemplateHeight / 2.0f) + tempTemplateHeight / 2;
int rotateX = cos(radian) * ((float)x - (float)tempTemplateWidth / 2.0f) + sin(radian) * ((float)y - (float)tempTemplateHeight / 2.0f) + tempTemplateWidth / 2;
if(rotateY < tempTemplateHeight && rotateX < tempTemplateWidth && rotateY >= 0 && rotateX >= 0)
rotateBinaryTemplateImage->imageData[scale] = tempBinaryTemplateImage->imageData[rotateY * tempTemplateWidth + rotateX];
}
}
//cvShowImage(windowNameSource, rotateBinaryTemplateImage);
//cvWaitKey(0);
cvMatchTemplate(binarySourceImage, rotateBinaryTemplateImage, result, CV_TM_SQDIFF_NORMED);
//cvMatchTemplate(binarySourceImage, rotateBinaryTemplateImage, result, CV_TM_SQDIFF);
cvMinMaxLoc(result, &minVal, NULL, &minLoc, NULL, NULL);
printf(": %f%%\n", (int)(i * 0.5 * 100), j * 20, (1 - minVal) * 100);
if(minVal < 0.065) // 1 - 0.065 = 0.935 : 93.5%
{
tempLoc.x = minLoc.x + tempTemplateWidth;
tempLoc.y = minLoc.y + tempTemplateHeight;
cvRectangle(destinationImage, minLoc, tempLoc, CV_RGB(0, 255, 0), 1, 8, 0);
}
}
//cvShowImage(windowNameSource, result);
//cvWaitKey(0);
cvReleaseImage(&tempBinaryTemplateImage);
cvReleaseImage(&result);
}
// cvShowImage(windowNameSource, sourceImage);
// cvShowImage(windowNameCoefficientOfCorrelation, result);
cvShowImage(windowNameDestination, destinationImage);
key = cvWaitKey(0);
cvReleaseImage(&sourceImage);
cvReleaseImage(&templateImage);
cvReleaseImage(&graySourceImage);
cvReleaseImage(&grayTemplateImage);
cvReleaseImage(&binarySourceImage);
cvReleaseImage(&binaryTemplateImage);
cvReleaseImage(&destinationImage);
cvDestroyWindow(windowNameSource);
cvDestroyWindow(windowNameDestination);
cvDestroyWindow(windowNameCoefficientOfCorrelation);
}
结果:
模板图片:
结果图像:
上面的函数在此图像中的完美匹配(角度和比例不变)周围放置矩形......
The function above puts rectangles around the perfect matches (angle and scale invariant) in this image .....
现在，我一直在尝试将代码移植到 C++ 接口中.如果有人需要更多详细信息，请告诉我.
Now, I have been trying to port the code into C++ interface. If anyone needs more details please let me know.
推荐答案
以上代码的C++移植:
C++ Port of above code:
Mat TemplateMatch(Mat sourceImage, Mat templateImage){
double minVal;
Point minLoc;
Point tempLoc;
Mat graySourceImage = Mat(sourceImage.size(),CV_8UC1);
Mat grayTemplateImage = Mat(templateImage.size(),CV_8UC1);
Mat binarySourceImage = Mat(sourceImage.size(),CV_8UC1);
Mat binaryTemplateImage = Mat(templateImage.size(),CV_8UC1);
Mat destinationImage = Mat(sourceImage.size(),CV_8UC3);
sourceImage.copyTo(destinationImage);
cvtColor(sourceImage, graySourceImage, CV_BGR2GRAY);
cvtColor(templateImage, grayTemplateImage, CV_BGR2GRAY);
threshold(graySourceImage, binarySourceImage, 200, 255, CV_THRESH_OTSU );
threshold(grayTemplateImage, binaryTemplateImage, 200, 255, CV_THRESH_OTSU);
int templateHeight = templateImage.rows;
int templateWidth = templateImage.cols;
float templateScale = 0.5f;
for(int i = 2; i <= 3; i++){
int tempTemplateHeight = (int)(templateWidth * (i * templateScale));
int tempTemplateWidth = (int)(templateHeight * (i * templateScale));
Mat tempBinaryTemplateImage = Mat(Size(tempTemplateWidth,tempTemplateHeight),CV_8UC1);
Mat result = Mat(Size(sourceImage.cols - tempTemplateWidth + 1,sourceImage.rows - tempTemplateHeight + 1),CV_32FC1);
resize(binaryTemplateImage,tempBinaryTemplateImage,Size(tempBinaryTemplateImage.cols,tempBinaryTemplateImage.rows),0,0,INTER_LINEAR);
float degree = 20.0f;
for(int j = 0; j <= 9; j++){
Mat rotateBinaryTemplateImage = Mat(Size(tempBinaryTemplateImage.cols, tempBinaryTemplateImage.rows), CV_8UC1);
for(int y = 0; y < tempTemplateHeight; y++){
for(int x = 0; x < tempTemplateWidth; x++){
rotateBinaryTemplateImage.data[y * tempTemplateWidth + x] = 255;
}
}
for(int y = 0; y < tempTemplateHeight; y++){
for(int x = 0; x < tempTemplateWidth; x++){
float radian = (float)j * degree * CV_PI / 180.0f;
int scale = y * tempTemplateWidth + x;
int rotateY = - sin(radian) * ((float)x - (float)tempTemplateWidth / 2.0f) + cos(radian) * ((float)y - (float)tempTemplateHeight / 2.0f) + tempTemplateHeight / 2;
int rotateX = cos(radian) * ((float)x - (float)tempTemplateWidth / 2.0f) + sin(radian) * ((float)y - (float)tempTemplateHeight / 2.0f) + tempTemplateWidth / 2;
if(rotateY < tempTemplateHeight && rotateX < tempTemplateWidth && rotateY >= 0 && rotateX >= 0)
rotateBinaryTemplateImage.data[scale] = tempBinaryTemplateImage.data[rotateY * tempTemplateWidth + rotateX];
}
}
matchTemplate(binarySourceImage, rotateBinaryTemplateImage, result, CV_TM_SQDIFF_NORMED);
minMaxLoc(result, &minVal, 0, &minLoc, 0, Mat());
cout<<(int)(i * 0.5 * 100)<<" , "<< j * 20<<" , "<< (1 - minVal) * 100<<endl;
if(minVal < 0.065){ // 1 - 0.065 = 0.935 : 93.5%
tempLoc.x = minLoc.x + tempTemplateWidth;
tempLoc.y = minLoc.y + tempTemplateHeight;
rectangle(destinationImage, minLoc, tempLoc, CV_RGB(0, 255, 0), 1, 8, 0);
}
}
}
return destinationImage;
}
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