lena.png:
pattern.png:
class MatchingDemo {
public void run(String inFile, String templateFile, String outFile,
int match_method) {
System.out.println("\nRunning Template Matching");
Mat img = Highgui.imread(inFile);
Mat templ = Highgui.imread(templateFile);
// / Create the result matrix
int result_cols = img.cols() - templ.cols() + 1;
int result_rows = img.rows() - templ.rows() + 1;
Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1);
// / Do the Matching and Normalize
Imgproc.matchTemplate(img, templ, result, match_method);
Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat());
Highgui.imwrite("out2.png", result);
// / Localizing the best match with minMaxLoc
MinMaxLocResult mmr = Core.minMaxLoc(result);
Point matchLoc;
if (match_method == Imgproc.TM_SQDIFF
|| match_method == Imgproc.TM_SQDIFF_NORMED) {
matchLoc = mmr.minLoc;
System.out.println(mmr.minVal);
} else {
matchLoc = mmr.maxLoc;
System.out.println(mmr.maxVal);
}
// / Show me what you got
Core.rectangle(img, matchLoc, new Point(matchLoc.x + templ.cols(),
matchLoc.y + templ.rows()), new Scalar(0, 255, 0));
// Save the visualized detection.
System.out.println("Writing " + outFile);
Highgui.imwrite(outFile, img);
}
}
public class TemplateMatching {
public static void main(String[] args) {
System.loadLibrary("opencv_java249");
new MatchingDemo().run("lena.png", "pattern.png", "output.png", Imgproc.TM_CCOEFF);
}
}