java - 在 Android 中使用 OpenCV 进行实时纸张检测

Question

首先我非常感谢博客 http://opencv-code.com/tutorials/automatic-perspective-correction-for-quadrilateral-objects/

我正在关注这个，但我没有处理 image (Used in the blog above)但是，我试图在实时相机预览中检测任何尺寸的纸张(A4、合法或任何普通矩形纸张尺寸)。

我遇到的问题是在“扩展 hough 线段以适合图像”之后我得到了大量的 hough 线，因此得到超过 4 个相交点(不是 == 4)。

像这样http://s17.postimg.org/i0a57fb8v/device_2015_04_07_171351.png

如何删除其余无效点，我只需要 4 个角点？我正在使用适用于 Android 的 OpenCV 库

请主要关注detectPaperSheet() 方法。这是我的代码:

 package org.opencv.samples.tutorial1;

import java.util.ArrayList;

import org.opencv.android.BaseLoaderCallback;
import org.opencv.android.CameraBridgeViewBase;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewFrame;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewListener2;
import org.opencv.android.LoaderCallbackInterface;
import org.opencv.android.OpenCVLoader;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;

import android.app.Activity;
import android.os.Bundle;
import android.util.Log;
import android.view.Menu;
import android.view.MenuItem;
import android.view.SurfaceView;
import android.view.WindowManager;
import android.widget.Toast;

public class Tutorial1Activity extends Activity implements
        CvCameraViewListener2 {
    private static final String TAG = "OCVSample::Activity";

private CameraBridgeViewBase mOpenCvCameraView;
private boolean mIsJavaCamera = true;
private MenuItem mItemSwitchCamera = null;

private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
    @Override
    public void onManagerConnected(int status) {
        switch (status) {
        case LoaderCallbackInterface.SUCCESS: {
            Log.i(TAG, "OpenCV loaded successfully");
            mOpenCvCameraView.enableView();
        }
            break;
        default: {
            super.onManagerConnected(status);
        }
            break;
        }
    }
};

public Tutorial1Activity() {
    Log.i(TAG, "Instantiated new " + this.getClass());
}

/** Called when the activity is first created. */
@Override
public void onCreate(Bundle savedInstanceState) {
    Log.i(TAG, "called onCreate");
    super.onCreate(savedInstanceState);
    getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);

    setContentView(R.layout.tutorial1_surface_view);

    if (mIsJavaCamera)
        mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.tutorial1_activity_java_surface_view);
    else
        mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.tutorial1_activity_native_surface_view);

    mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);

    mOpenCvCameraView.setCvCameraViewListener(this);
}

@Override
public void onPause() {
    super.onPause();
    if (mOpenCvCameraView != null)
        mOpenCvCameraView.disableView();
}

@Override
public void onResume() {
    super.onResume();
    OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_9, this,
            mLoaderCallback);
}

public void onDestroy() {
    super.onDestroy();
    if (mOpenCvCameraView != null)
        mOpenCvCameraView.disableView();
}

@Override
public boolean onCreateOptionsMenu(Menu menu) {
    Log.i(TAG, "called onCreateOptionsMenu");
    mItemSwitchCamera = menu.add("Toggle Native/Java camera");
    return true;
}

@Override
public boolean onOptionsItemSelected(MenuItem item) {
    String toastMesage = new String();
    Log.i(TAG, "called onOptionsItemSelected; selected item: " + item);

    if (item == mItemSwitchCamera) {
        mOpenCvCameraView.setVisibility(SurfaceView.GONE);
        mIsJavaCamera = !mIsJavaCamera;

        if (mIsJavaCamera) {
            mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.tutorial1_activity_java_surface_view);
            toastMesage = "Java Camera";
        } else {
            mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.tutorial1_activity_native_surface_view);
            toastMesage = "Native Camera";
        }

        mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
        mOpenCvCameraView.setCvCameraViewListener(this);
        mOpenCvCameraView.enableView();
        Toast toast = Toast.makeText(this, toastMesage, Toast.LENGTH_LONG);
        toast.show();
    }

    return true;
}

public void onCameraViewStarted(int width, int height) {
}

public void onCameraViewStopped() {
}

public Mat onCameraFrame(CvCameraViewFrame inputFrame) {

    return detectPaperSheet(inputFrame.rgba());

}

private Mat detectPaperSheet(Mat original_image) {
    Mat imgSource = original_image;
    Mat untouched = original_image.clone();

    // Converting to grayscale
    Mat mHsvMat = new Mat(imgSource.rows(), imgSource.cols(),
            CvType.CV_8UC1, new Scalar(0));

    Imgproc.cvtColor(imgSource, mHsvMat, Imgproc.COLOR_BGRA2GRAY, 4);

    // apply gaussian blur to smoothen lines of dots
    Imgproc.GaussianBlur(imgSource, imgSource, new Size(11, 11), 0);

    // Applying Canny
    Imgproc.Canny(mHsvMat, mHsvMat, 80, 100);

    Mat lines = new Mat();
    int threshold = 100;
    int minLineSize = 150;
    int lineGap = 40;

    Imgproc.HoughLinesP(mHsvMat, lines, 1, Math.PI / 180, threshold,
            minLineSize, lineGap);

    // Expanding the Lines To Image Width and Height

    ArrayList<Point> corners = new ArrayList<Point>();

    for (int x = 0; x < lines.cols(); x++) {

        double[] vec = lines.get(0, x);
        double[] val = new double[4];

        val[0] = 0;
        val[1] = ((float) vec[1] - vec[3]) / (vec[0] - vec[2]) * -vec[0]
                + vec[1];
        val[2] = imgSource.cols();
        val[3] = ((float) vec[1] - vec[3]) / (vec[0] - vec[2])
                * (imgSource.cols() - vec[2]) + vec[3];

        lines.put(0, x, val);
    }

    for (int x = 0; x < lines.cols(); x++) {
        double[] vec = lines.get(0, x);
        double x1 = vec[0], y1 = vec[1], x2 = vec[2], y2 = vec[3];
        Point start = new Point(x1, y1);
        Point end = new Point(x2, y2);

        Core.line(imgSource, start, end, new Scalar(255, 0, 0), 1);

    }

    for (int i = 0; i < lines.cols(); i++) {
        for (int j = i + 1; j < lines.cols(); j++) {
            Point pt = computeIntersect(lines.get(0, i), lines.get(0, j));
            if (pt.x >= 0 && pt.y >= 0)
                corners.add(pt);
        }
    }

    if (corners.size() < 4) {
        Log.e("Corner < 4", corners.size() + " |");
        return untouched;
    } else {
        Log.e("Corner > 4", corners.size() + " |");
    }

    //Mat cornerPoints = new Mat();

    for (int j = 0; j < corners.size(); j++) {

        Core.circle(imgSource,
                new Point(corners.get(j).x, corners.get(j).y), 20,
                new Scalar(0, 0, 255), 2);
    }

    return imgSource;
}

private static Point computeIntersect(double[] a, double[] b) {
    double x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3], x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3];
    double denom = ((x1 - x2) * (y3 - y4)) - ((y1 - y2) * (x3 - x4));
    Point pt = new Point();
    if (denom != 0) {

        pt.x = ((x1 * y2 - y1 * x2) * (x3 - x4) - (x1 - x2)
                * (x3 * y4 - y3 * x4))
                / denom;
        pt.y = ((x1 * y2 - y1 * x2) * (y3 - y4) - (y1 - y2)
                * (x3 * y4 - y3 * x4))
                / denom;
        return pt;
    } else
        return new Point(-1, -1);
}

}

Answer 1

我记得poly approximation在这种情况下(检测矩形)对我有一些帮助。但是我将它与 findContours 一起使用方法(使用 CV_CHAIN_APPROX_SIMPLE 模式)，因为它似乎比 Hough 线产生更好的结果。

[编辑] 我在 C++ 中使用 JNI 完成了它，但在 Java 中我认为它应该看起来像这样:

    Mat srcImg; //you may want to apply Canny or some threshold before searching for contours
    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Mat hierarchy;
    Imgproc.findContours(srcImg, contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
    MatOfPoint2f mat2fsrc, mat2fdst;
    Scalar color =  new Scalar(250, 250, 255);

    for (int i = 0; i < contours.size(); i++) {
        contours.get(i).convertTo(mat2fsrc, CvType.CV_32FC2);
        Imgproc.approxPolyDP(mat2fsrc, mat2fdst, 0.01 * Imgproc.arcLength(mat2fsrc, true), true);
        mat2fdst.convertTo(contours.get(i), CvType.CV_32S);
        Imgproc.drawContours(srcImg, contours, i, color, 2, 8, hierarchy, 0, new Point());
    }