public static BufferedImage bufferedImage(Mat m) {
int type = BufferedImage.TYPE_BYTE_GRAY;
if (m.channels() > 1) {
type = BufferedImage.TYPE_3BYTE_BGR;
}
BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
m.get(
0, 0, ((DataBufferByte) image.getRaster().getDataBuffer()).getData()); // get all the pixels
return image;
}
public void templateMatching() {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
int match_method = 5;
int max_Trackbar = 5;
Mat data = Highgui.imread("images/training_data/1" + "/data (" + 1 + ").jpg");
Mat temp = Highgui.imread("images/template.jpg");
Mat img = data.clone();
int result_cols = img.cols() - temp.cols() + 1;
int result_rows = img.rows() - temp.rows() + 1;
Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1);
Imgproc.matchTemplate(img, temp, result, match_method);
Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat());
double minVal;
double maxVal;
Point minLoc;
Point maxLoc;
Point matchLoc;
// minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );
Core.MinMaxLocResult res = Core.minMaxLoc(result);
if (match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED) {
matchLoc = res.minLoc;
} else {
matchLoc = res.maxLoc;
}
// / Show me what you got
Core.rectangle(
img,
matchLoc,
new Point(matchLoc.x + temp.cols(), matchLoc.y + temp.rows()),
new Scalar(0, 255, 0));
// Save the visualized detection.
Highgui.imwrite("images/samp.jpg", img);
}
public void copyMat(Mat src, Mat dest) {
int srcRows = src.rows();
int srcCols = src.cols();
int destRows = dest.rows();
int destCols = dest.cols();
for (int i = 0; i < srcRows; i++) {
for (int j = 0; j < srcCols; j++) {
double bit = src.get(i, j)[0];
dest.put(i, j, bit);
System.out.println(bit);
}
}
}
public static Mat getCCH(Mat image) {
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
image, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
Mat chainHistogram = Mat.zeros(1, 8, CvType.CV_32F);
int n = 0;
MatOfPoint2f approxCurve = new MatOfPoint2f();
for (MatOfPoint contour : contours) {
// get the freeman chain code from the contours
int rows = contour.rows();
// System.out.println("\nrows"+rows+"\n"+contour.dump());
int direction = 7;
Mat prevPoint = contours.get(0).row(0);
n += rows - 1;
for (int i = 1; i < rows; i++) {
// get the current point
double x1 = contour.get(i - 1, 0)[1];
double y1 = contour.get(i - 1, 0)[0];
// get the second point
double x2 = contour.get(i, 0)[1];
double y2 = contour.get(i, 0)[0];
if (x2 == x1 && y2 == y1 + 1) direction = 0;
else if (x2 == x1 - 1 && y2 == y1 + 1) direction = 1;
else if (x2 == x1 - 1 && y2 == y1) direction = 2;
else if (x2 == x1 - 1 && y2 == y1 - 1) direction = 3;
else if (x2 == x1 && y2 == y1 - 1) direction = 4;
else if (x2 == x1 + 1 && y2 == y1 - 1) direction = 5;
else if (x2 == x1 + 1 && y2 == y1) direction = 6;
else if (x2 == x1 + 1 && y2 == y1 + 1) direction = 7;
else System.out.print("err");
double counter = chainHistogram.get(0, direction)[0];
chainHistogram.put(0, direction, ++counter);
System.out.print(direction);
}
}
System.out.println("\n" + chainHistogram.dump());
Scalar alpha = new Scalar(n); // the factor
Core.divide(chainHistogram, alpha, chainHistogram);
System.out.println("\nrows=" + n + " " + chainHistogram.dump());
return chainHistogram;
}
public static void main(String[] args) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Mat mat = Mat.eye( 3, 3, CvType.CV_8UC1 );
// System.out.println( "mat = " + mat.dump() );
Sample n = new Sample();
// n.templateMatching();
// put text in image
// Mat data= Highgui.imread("images/erosion.jpg");
// Core.putText(data, "Sample", new Point(50,80), Core.FONT_HERSHEY_SIMPLEX, 1, new
// Scalar(0,0,0),2);
//
// Highgui.imwrite("images/erosion2.jpg", data);
// getting dct of an image
String path = "images/croppedfeature/go (20).jpg";
path = "images/wordseg/img1.png";
Mat image = Highgui.imread(path, Highgui.IMREAD_GRAYSCALE);
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.threshold(image, image, 0, 255, Imgproc.THRESH_OTSU);
Imgproc.threshold(image, image, 220, 128, Imgproc.THRESH_BINARY_INV);
Mat newImg = new Mat(45, 100, image.type());
newImg.setTo(new Scalar(0));
n.copyMat(image, newImg);
int vgap = 25;
int hgap = 45 / 3;
Moments m = Imgproc.moments(image, false);
Mat hu = new Mat();
Imgproc.HuMoments(m, hu);
System.out.println(hu.dump());
// //divide the mat into 12 parts then get the features of each part
// int count=1;
// for(int j=0; j<45; j+=hgap){
// for(int i=0;i<100;i+=vgap){
// Mat result = newImg.submat(j, j+hgap, i, i+vgap);
//
//
// Moments m= Imgproc.moments(result, false);
// double m01= m.get_m01();
// double m00= m.get_m00();
// double m10 = m.get_m10();
// int x= m00!=0? (int)(m10/m00):0;
// int y= m00!=0? (int)(m01/m00):0;
// Mat hu= new Mat();
// Imgproc.HuMoments(m, hu);
// System.out.println(hu.dump());
// System.out.println(count+" :"+x+" and "+y);
// Imgproc.threshold(result, result, 0,254, Imgproc.THRESH_BINARY_INV);
// Highgui.imwrite("images/submat/"+count+".jpg", result);
// count++;
//
// }
// }
//
// for(int i=vgap;i<100;i+=vgap){
// Point pt1= new Point(i, 0);
// Point pt2= new Point(i, 99);
// Core.line(newImg, pt1, pt2, new Scalar(0,0,0));
// }
// for(int i=hgap;i<45;i+=hgap){
// Point pt1= new Point(0, i);
// Point pt2= new Point(99, i);
// Core.line(newImg, pt1, pt2, new Scalar(0,0,0));
// }
// Highgui.imwrite("images/submat/copyto.jpg", newImg);
}