Question

我正在使用OpenCV4Android版本2.4.11，我正在尝试检测从Camera中检索到的帧中的矩形。我在这个网站上提到了一些问题，他们非常乐于助人。但我目前面临的问题是当我尝试检测中间的浅色物体时，如下图中的原始图像所示，在这种情况下，检测算法不检测整个物体，而是检测到它的暗部分，如标题部分中的图像所示“处理”下面。

下面发布的代码表示我遵循的步骤以及用于检测帧中对象的阈值。

请让我知道为什么整个物体没有被检测到，我该如何检测整个物体而不仅仅是它的一部分

码：

    //step 1
    this.mMatGray = new Mat();
    Imgproc.cvtColor(this.mMatInputFrame, this.mMatGray, Imgproc.COLOR_BGR2GRAY);
    //step 2
    this.mMatEdges = new Mat();
    Imgproc.blur(this.mMatGray, this.mMatEdges, new Size(7, 7));//7,7
    //step 3
    Imgproc.Canny(this.mMatEdges, this.mMatEdges, 128, 128*2, 5, true);//..,..,2,900,7,true
    //step 4
    dilated = new Mat();
    Mat dilateElement = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE, new Size(3, 3));
    Imgproc.dilate(mMatEdges, dilated, dilateElement);

     ArrayList<MatOfPoint> contours = new ArrayList<>();
    hierachy = new Mat();
    Imgproc.findContours(dilated, contours, hierachy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);

    MatOfPoint2f approxCurve = new MatOfPoint2f();
    if (contours.size() > 0) {
        for (int i = 0; i < contours.size(); i++) {

            MatOfPoint2f contour2f = new MatOfPoint2f(contours.get(i).toArray());
            double approxDistance = Imgproc.arcLength(contour2f, true) * .02;//.02
            Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
            MatOfPoint points = new MatOfPoint(approxCurve.toArray());

            if (points.total() >= 4 && Imgproc.isContourConvex(points) && Math.abs(Imgproc.contourArea(points)) >= 40000 && Math.abs(Imgproc.contourArea(points)) <= 150000) {
                Rect boundingRect = Imgproc.boundingRect(points);
                RotatedRect minAreaRect = Imgproc.minAreaRect(contour2f);
                Point[] rectPoints = new Point[4];
                minAreaRect.points(rectPoints);
                Rect minAreaAsRect = minAreaRect.boundingRect();

                //to draw the minAreaRect
                for( int j = 0; j < 4; j++ ) {
                    Core.line(mMatInputFrame, rectPoints[j], rectPoints[(j+1)%4], new Scalar(255,0,0));
                }
                Core.putText(mMatInputFrame, "MinAreaRect", new Point(10, 30), 1,1 , new Scalar(255,0,0),2);
                Core.putText(mMatInputFrame, "Width: " + minAreaAsRect.width , new Point(minAreaAsRect.tl().x, minAreaAsRect.tl().y-100), 1,1 , new Scalar(255,0,0),2);
                Core.putText(mMatInputFrame, "Height: " + minAreaAsRect.height, new Point(minAreaAsRect.tl().x, minAreaAsRect.tl().y-80), 1,1 , new Scalar(255,0,0),2);
                Core.putText(mMatInputFrame, "Area: " + minAreaAsRect.area(), new Point(minAreaAsRect.tl().x, minAreaAsRect.tl().y-60), 1,1 , new Scalar(255,0,0),2);

                //drawing the contour
                Imgproc.drawContours(mMatInputFrame,  contours, i, new Scalar(0,0,0),2);

                //drawing the boundingRect
                Core.rectangle(mMatInputFrame, boundingRect.tl(), boundingRect.br(), new Scalar(0, 255, 0), 1, 1, 0);
                Core.putText(mMatInputFrame, "BoundingRect", new Point(10, 60), 1,1 , new Scalar(0,255,0),2);
                Core.putText(mMatInputFrame, "Width: " + boundingRect.width , new Point(boundingRect.br().x-100, boundingRect.tl().y-100), 1,1 , new Scalar(0,255,0),2);
                Core.putText(mMatInputFrame, "Height: " + boundingRect.height, new Point(boundingRect.br().x-100, boundingRect.tl().y-80), 1,1 , new Scalar(0,255,0),2);
                Core.putText(mMatInputFrame, "Area: " + Imgproc.contourArea(points), new Point(boundingRect.br().x-100, boundingRect.tl().y-60), 1,1 , new Scalar(0,255,0),2);
            }
        }
    }

原始图片：

已处理的图片：

Answer 1

我用c ++实现了。 API是相同的，所以你可以轻松移植到Android。我使用过Opencv 2.4.8。请检查实施情况。希望代码说明做了什么：

#include <iostream>
#include <string>
#include "opencv/highgui.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"

using namespace std;
using namespace cv;


Mat GetKernel(int erosion_size)
{
       Mat element = getStructuringElement(cv::MORPH_CROSS,
              cv::Size(2 * erosion_size + 1, 2 * erosion_size + 1),
              cv::Point(erosion_size, erosion_size) );

       return element;
}
int main()
{
    Mat img = imread("C:/Users/dell2/Desktop/j6B3A.png",0);//loading gray scale image
    Mat imgC = imread("C:/Users/dell2/Desktop/j6B3A.png",1);
    GaussianBlur(img,img,Size(7,7),1.5,1.5);

    Mat dimg;
    adaptiveThreshold(img,dimg,255,ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY,17,1);



       dilate(dimg,img,GetKernel(2)); 
       erode(img,dimg,GetKernel(2)); 
       erode(dimg,img,GetKernel(1)); 


       dimg = img;

    //*
     vector<vector<Point>> contours; // Vector for storing contour
    vector<Vec4i> hierarchy;

    findContours( dimg, contours, hierarchy,CV_RETR_TREE , CV_CHAIN_APPROX_NONE ); // Find the contours in the image

     double largest_area = 0;
     int largest_contour_index = 0;
     Rect bounding_rect;

     for( int i = 0; i< contours.size(); i++ ) // iterate through each contour. 
      {
       double a=contourArea( contours[i],false);  //  Find the area of contour
       if(a>largest_area){
       largest_area=a;
       largest_contour_index=i;                //Store the index of largest contour
       bounding_rect=boundingRect(contours[i]); // Find the bounding rectangle for biggest contour
       }

      }

     drawContours( imgC, contours, largest_contour_index, Scalar(255,0,0), 2, 8, hierarchy, 0, Point() );
    rectangle(imgC, bounding_rect,  Scalar(0,255,0),2, 8,0);  
 /**/

    //imshow("display",dimg);
    imshow("display2",imgC);
    waitKey(0);
    return 0;
}

产生的结果：

如有必要，您可以微调阈值。

如何检测框架中的整个矩形

1 个答案: