Android OpenCV纸张检测

Question

我想这个问题是问之前，但我没有找到一个样本或解决方案为我的问题。我是opencv的新手，我想使用opencv CameraPreview进行纸张检测。在我的示例应用程序中，我使用静态初始化的opencv 3.0.0。我知道物体识别可以通过以下步骤完成:

1. 设置输入图像为Canny
2. 模糊Canny图像
3. 查找模糊Canny图像上的轮廓
4. 查找矩形等
5. 绘制线条或用半透明颜色填充矩形

我的问题是，现在我可以狡猾和模糊的图像，但我不知道如何找到轮廓和矩形和填充它们与半透明的颜色。

这是我当前的onCameraFrame函数:

@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
    Mat input = inputFrame.rgba();
    Mat output = input.clone();
    Imgproc.Canny(input, output, 50, 50);
    Imgproc.blur(output, output,new Size(5,5));
    //Find Contours
    //Search for biggest Contour/Rectangle
    //Fill Rectangle with half transparent Color
    return output;
}

谁能帮我解决纸张检测的问题，并有一个代码样本为android/java?谢谢你

Answer 1

以下代码来自我正在开发的Open Note Scanner应用程序，您可以使用它来查找更多信息。

函数findDocument将返回一个四边形对象，该对象封装了包含轮廓的MatOfPoint和包含单个点的Point[]。你可以调用它，并使用返回的对象调用Imgproc.drawContours()来完成你的图像。

所有的代码都是基于pyimagesearch这个优秀的教程编写的

注意:这是从我的代码中快速移植的方法，它没有语法错误，但我没有测试它。

package com.todobom.opennotescanner.views;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
public class detectDocument {
    /**
     *  Object that encapsulates the contour and 4 points that makes the larger
     *  rectangle on the image
     */
    public static class Quadrilateral {
        public MatOfPoint contour;
        public Point[] points;
        public Quadrilateral(MatOfPoint contour, Point[] points) {
            this.contour = contour;
            this.points = points;
        }
    }
    public static Quadrilateral findDocument( Mat inputRgba ) {
        ArrayList<MatOfPoint> contours = findContours(inputRgba);
        Quadrilateral quad = getQuadrilateral(contours);
        return quad;
    }
    private static ArrayList<MatOfPoint> findContours(Mat src) {
        double ratio = src.size().height / 500;
        int height = Double.valueOf(src.size().height / ratio).intValue();
        int width = Double.valueOf(src.size().width / ratio).intValue();
        Size size = new Size(width,height);
        Mat resizedImage = new Mat(size, CvType.CV_8UC4);
        Mat grayImage = new Mat(size, CvType.CV_8UC4);
        Mat cannedImage = new Mat(size, CvType.CV_8UC1);
        Imgproc.resize(src,resizedImage,size);
        Imgproc.cvtColor(resizedImage, grayImage, Imgproc.COLOR_RGBA2GRAY, 4);
        Imgproc.GaussianBlur(grayImage, grayImage, new Size(5, 5), 0);
        Imgproc.Canny(grayImage, cannedImage, 75, 200);
        ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
        Mat hierarchy = new Mat();
        Imgproc.findContours(cannedImage, contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
        hierarchy.release();
        Collections.sort(contours, new Comparator<MatOfPoint>() {
            @Override
            public int compare(MatOfPoint lhs, MatOfPoint rhs) {
                return Double.valueOf(Imgproc.contourArea(rhs)).compareTo(Imgproc.contourArea(lhs));
            }
        });
        resizedImage.release();
        grayImage.release();
        cannedImage.release();
        return contours;
    }
    private static Quadrilateral getQuadrilateral(ArrayList<MatOfPoint> contours) {
        for ( MatOfPoint c: contours ) {
            MatOfPoint2f c2f = new MatOfPoint2f(c.toArray());
            double peri = Imgproc.arcLength(c2f, true);
            MatOfPoint2f approx = new MatOfPoint2f();
            Imgproc.approxPolyDP(c2f, approx, 0.02 * peri, true);
            Point[] points = approx.toArray();
            // select biggest 4 angles polygon
            if (points.length == 4) {
                Point[] foundPoints = sortPoints(points);
                return new Quadrilateral(c, foundPoints);
            }
        }
        return null;
    }
    private static Point[] sortPoints(Point[] src) {
        ArrayList<Point> srcPoints = new ArrayList<>(Arrays.asList(src));
        Point[] result = { null , null , null , null };
        Comparator<Point> sumComparator = new Comparator<Point>() {
            @Override
            public int compare(Point lhs, Point rhs) {
                return Double.valueOf(lhs.y + lhs.x).compareTo(rhs.y + rhs.x);
            }
        };
        Comparator<Point> diffComparator = new Comparator<Point>() {
            @Override
            public int compare(Point lhs, Point rhs) {
                return Double.valueOf(lhs.y - lhs.x).compareTo(rhs.y - rhs.x);
            }
        };
        // top-left corner = minimal sum
        result[0] = Collections.min(srcPoints, sumComparator);
        // bottom-right corner = maximal sum
        result[2] = Collections.max(srcPoints, sumComparator);
        // top-right corner = minimal diference
        result[1] = Collections.min(srcPoints, diffComparator);
        // bottom-left corner = maximal diference
        result[3] = Collections.max(srcPoints, diffComparator);
        return result;
    }
}