问题
This might have been answered but I desperately need an answer for this. I want to find the largest square or rectangle in an image using OpenCV in Android. All of the solutions that I found are C++ and I tried converting it but it doesn't work and I do not know where I'm wrong.
private Mat findLargestRectangle(Mat original_image) {
Mat imgSource = original_image;
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);
Imgproc.Canny(imgSource, imgSource, 100, 100);
//I don't know what to do in here
return imgSource;
}
What I am trying to accomplish in here is to create a new image that is based on the largest square found in the original image (return value Mat image).
This is what I want to happen:
1 http://img14.imageshack.us/img14/7855/s7zr.jpg
It's also okay that I just get the four points of the largest square and I think I can take it from there. But it would be better if I can just return the cropped image.
回答1:
After canny
1- you need to reduce noises with gaussian blur and find all the contours
2- find and list all the contours' areas.
3- the largest contour will be nothing but the painting.
4- now use perpective transformation to transform your shape to a rectangle.
check sudoku solver examples to see the similar processing problem. (largest contour + perspective)
回答2:
Took me a while to convert the C++ code to Java, but here it is :-)
Warning ! Raw code, totally not optimized and all.
I decline any liability in cases of injury or lethal accident
List<MatOfPoint> squares = new ArrayList<MatOfPoint>();
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
if (Math.random()>0.80) {
findSquares(inputFrame.rgba().clone(),squares);
}
Mat image = inputFrame.rgba();
Imgproc.drawContours(image, squares, -1, new Scalar(0,0,255));
return image;
}
int thresh = 50, N = 11;
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
double angle( Point pt1, Point pt2, Point pt0 ) {
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/Math.sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
void findSquares( Mat image, List<MatOfPoint> squares )
{
squares.clear();
Mat smallerImg=new Mat(new Size(image.width()/2, image.height()/2),image.type());
Mat gray=new Mat(image.size(),image.type());
Mat gray0=new Mat(image.size(),CvType.CV_8U);
// down-scale and upscale the image to filter out the noise
Imgproc.pyrDown(image, smallerImg, smallerImg.size());
Imgproc.pyrUp(smallerImg, image, image.size());
// find squares in every color plane of the image
for( int c = 0; c < 3; c++ )
{
extractChannel(image, gray, c);
// try several threshold levels
for( int l = 1; l < N; l++ )
{
//Cany removed... Didn't work so well
Imgproc.threshold(gray, gray0, (l+1)*255/N, 255, Imgproc.THRESH_BINARY);
List<MatOfPoint> contours=new ArrayList<MatOfPoint>();
// find contours and store them all as a list
Imgproc.findContours(gray0, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
MatOfPoint approx=new MatOfPoint();
// test each contour
for( int i = 0; i < contours.size(); i++ )
{
// approximate contour with accuracy proportional
// to the contour perimeter
approx = approxPolyDP(contours.get(i), Imgproc.arcLength(new MatOfPoint2f(contours.get(i).toArray()), true)*0.02, true);
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if( approx.toArray().length == 4 &&
Math.abs(Imgproc.contourArea(approx)) > 1000 &&
Imgproc.isContourConvex(approx) )
{
double maxCosine = 0;
for( int j = 2; j < 5; j++ )
{
// find the maximum cosine of the angle between joint edges
double cosine = Math.abs(angle(approx.toArray()[j%4], approx.toArray()[j-2], approx.toArray()[j-1]));
maxCosine = Math.max(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if( maxCosine < 0.3 )
squares.add(approx);
}
}
}
}
}
void extractChannel(Mat source, Mat out, int channelNum) {
List<Mat> sourceChannels=new ArrayList<Mat>();
List<Mat> outChannel=new ArrayList<Mat>();
Core.split(source, sourceChannels);
outChannel.add(new Mat(sourceChannels.get(0).size(),sourceChannels.get(0).type()));
Core.mixChannels(sourceChannels, outChannel, new MatOfInt(channelNum,0));
Core.merge(outChannel, out);
}
MatOfPoint approxPolyDP(MatOfPoint curve, double epsilon, boolean closed) {
MatOfPoint2f tempMat=new MatOfPoint2f();
Imgproc.approxPolyDP(new MatOfPoint2f(curve.toArray()), tempMat, epsilon, closed);
return new MatOfPoint(tempMat.toArray());
}
回答3:
There are some related questions here in SO. Check them out:
OpenCV C++/Obj-C: Detecting a sheet of paper / Square Detection
How do I recognize squares in this image?
There is also an example shipped with OpenCV:
- https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/cpp/squares.cpp?rev=4079
Once you have the rectangle, you can align the picture by computing the homography with the rectangle corners and applying a perspective transform.
来源：https://stackoverflow.com/questions/17512234/android-opencv-find-largest-square-or-rectangle