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How to extract width and height of outline in javacv?

I am developing a project to identify components using the javacv package (Opencv). I used the method to return a set of rectangles in the image as "CvSeq". I need to know how to do the following things.

  • How can I get each rectangle from method output (from CvSeq)?
  • How to access the length and width of a rectangle?

This is a method that returns rectangles.

public static CvSeq findSquares( final IplImage src,  CvMemStorage storage)
{

CvSeq squares = new CvContour();
squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage);

IplImage pyr = null, timg = null, gray = null, tgray;
timg = cvCloneImage(src);

CvSize sz = cvSize(src.width() & -2, src.height() & -2);
tgray = cvCreateImage(sz, src.depth(), 1);
gray = cvCreateImage(sz, src.depth(), 1);
pyr = cvCreateImage(cvSize(sz.width()/2, sz.height()/2), src.depth(), src.nChannels());

// down-scale and upscale the image to filter out the noise
cvPyrDown(timg, pyr, CV_GAUSSIAN_5x5);
cvPyrUp(pyr, timg, CV_GAUSSIAN_5x5);
cvSaveImage("ha.jpg",   timg);
CvSeq contours = new CvContour();
// request closing of the application when the image window is closed
// show image on window
// find squares in every color plane of the image
for( int c = 0; c < 3; c++ )
{
    IplImage channels[] = {cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1)};
    channels[c] = cvCreateImage(sz, 8, 1);
    if(src.nChannels() > 1){
        cvSplit(timg, channels[0], channels[1], channels[2], null);
    }else{
        tgray = cvCloneImage(timg);
    }
    tgray = channels[c]; // try several threshold levels
    for( int l = 0; l < N; l++ )
    {
    //             hack: use Canny instead of zero threshold level.
    //             Canny helps to catch squares with gradient shading
                   if( l == 0 )
                {
    //                apply Canny. Take the upper threshold from slider
    //                and set the lower to 0 (which forces edges merging)
                      cvCanny(tgray, gray, 0, thresh, 5);
   //                 dilate canny output to remove potential
   //                // holes between edge segments
                      cvDilate(gray, gray, null, 1);
                 }
                 else
                 {
    //                apply threshold if l!=0:
                      cvThreshold(tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY);
                 }
    //            find contours and store them all as a list
                cvFindContours(gray, storage, contours, sizeof(CvContour.class), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);

                CvSeq approx;

  //            test each contour
                while (contours != null && !contours.isNull()) {
                       if (contours.elem_size() > 0) {
                            approx = cvApproxPoly(contours, Loader.sizeof(CvContour.class),storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0);
                    if( approx.total() == 4
                            &&
                            Math.abs(cvContourArea(approx, CV_WHOLE_SEQ, 0)) > 1000 &&
                        cvCheckContourConvexity(approx) != 0
                        ){
                        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(new CvPoint(cvGetSeqElem(approx, j%4)), new CvPoint(cvGetSeqElem(approx, j-2)), new CvPoint(cvGetSeqElem(approx, j-1))));
                       maxCosine = Math.max(maxCosine, cosine);
                         }
                         if( maxCosine < 0.2 ){
                             cvSeqPush(squares, approx);
                         }
                    }
                }
                contours = contours.h_next();
            }
        contours = new CvContour();
    }
}
return squares;
}

This is a sample of the original image that I used.

enter image description here

And this is the image that I got after drawing lines around the corresponding rectangles

enter image description here

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( OpenCV-Python):

import numpy as np
import cv2

im = cv2.imread('sofsqr.png')
img = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)

ret,thresh = cv2.threshold(img,127,255,1)

, . BINARY_INV (.. "1" ).

, :

enter image description here

. , , , .

, :

enter image description here

. ​​: [ x, y, , rect]

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:

contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

for cnt in contours:
    approx = cv2.approxPolyDP(cnt,cv2.arcLength(cnt,True)*0.02,True)
    if len(approx)==4:
        cv2.drawContours(im,[approx],0,(0,0,255),2)
        x,y,w,h = cv2.boundingRect(cnt)

EDIT:

, - .

, . .. , , . , , 10000. ( ). 10000, , , - , ( ).

for cnt in contours:
    approx = cv2.approxPolyDP(cnt,cv2.arcLength(cnt,True)*0.02,True)
    if len(approx)==4:
        x,y,w,h = cv2.boundingRect(approx)
        if w*h < 10000:
            cv2.drawContours(im,[approx],0,(0,0,255),-1)
        else:
            cv2.drawContours(im,[approx],0,(255,0,0),-1)

:

enter image description here

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+4

, , , :

IplImage channels[] = {cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1)};
channels[c] = cvCreateImage(sz, 8, 1);
if(src.nChannels() > 1){
    cvSplit(timg, channels[0], channels[1], channels[2], null);
}else{
    tgray = cvCloneImage(timg);
}
tgray = channels[c];

, , tgray . :

IplImage channels[] = {cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1), cvCreateImage(sz, 8, 1)};
channels[c] = cvCreateImage(sz, 8, 1);
if(src.nChannels() > 1){
    cvSplit(timg, channels[0], channels[1], channels[2], null);
    tgray = channels[c];
}else{
    tgray = cvCloneImage(timg);
}
+2

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