--- /dev/null
+#! /usr/bin/env octave
+##
+## The full "Square Detector" program.
+## It loads several images subsequentally and tries to find squares in
+## each image
+##
+
+cv;
+highgui;
+
+global g;
+
+g.thresh = 50;
+g.img = [];
+g.img0 = [];
+g.storage = [];
+g.wndname = "Square Detection Demo";
+
+function ret = compute_angle( pt1, pt2, pt0 )
+ dx1 = pt1.x - pt0.x;
+ dy1 = pt1.y - pt0.y;
+ dx2 = pt2.x - pt0.x;
+ dy2 = pt2.y - pt0.y;
+ ret = (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
+endfunction
+
+function squares = findSquares4( img, storage )
+ global g;
+ global cv;
+
+ N = 11;
+ sz = cvSize( img.width, img.height );
+ timg = cvCloneImage( img ); # make a copy of input image
+ gray = cvCreateImage( sz, 8, 1 );
+ pyr = cvCreateImage( cvSize(int32(sz.width/2), int32(sz.height/2)), 8, 3 );
+ ## create empty sequence that will contain points -
+ ## 4 points per square (the square's vertices)
+ squares = cvCreateSeq( 0, cv.sizeof_CvSeq, cv.sizeof_CvPoint, storage );
+ squares = cv.CvSeq_CvPoint.cast( squares );
+
+ ## select the maximum ROI in the image
+ ## with the width and height divisible by 2
+ subimage = cvGetSubRect( timg, cvRect( 0, 0, sz.width, sz.height ));
+
+ ## down-scale and upscale the image to filter out the noise
+ cvPyrDown( subimage, pyr, 7 );
+ cvPyrUp( pyr, subimage, 7 );
+ tgray = cvCreateImage( sz, 8, 1 );
+ ## find squares in every color plane of the image
+ for c=1:3,
+ ## extract the c-th color plane
+ channels = {[], [], []};
+ channels{c} = tgray;
+ cvSplit( subimage, channels{1}, channels{2}, channels{3}, [] ) ;
+ for l=1:N,
+ ## hack: use Canny instead of zero threshold level.
+ ## Canny helps to catch squares with gradient shading
+ if( l == 1 )
+ ## apply Canny. Take the upper threshold from slider
+ ## and set the lower to 0 (which forces edges merging)
+ cvCanny( tgray, gray, 0, g.thresh, 5 );
+ ## dilate canny output to remove potential
+ ## holes between edge segments
+ cvDilate( gray, gray, [], 1 );
+ else
+ ## apply threshold if l!=0
+ ## tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
+ cvThreshold( tgray, gray, l*255/N, 255, cv.CV_THRESH_BINARY );
+ endif
+
+ ## find contours and store them all as a list
+ [count, contours] = cvFindContours( gray, storage, cv.sizeof_CvContour, cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) );
+
+ if (!swig_this(contours))
+ continue;
+ endif
+
+ ## test each contour
+ for contour = CvSeq_hrange(contours),
+ ## approximate contour with accuracy proportional
+ ## to the contour perimeter
+ result = cvApproxPoly( contour, cv.sizeof_CvContour, storage, cv.CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 );
+ ## 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( result.total == 4 &&
+ abs(cvContourArea(result)) > 1000 &&
+ cvCheckContourConvexity(result) )
+ s = 0;
+ for i=1:5,
+ ## find minimum angle between joint
+ ## edges (maximum of cosine)
+ if( i > 2 )
+ t = abs(compute_angle( result{i}, result{i-2}, result{i-1}));
+ if (s<t)
+ s=t;
+ endif
+ endif
+ endfor
+ ## if cosines of all angles are small
+ ## (all angles are ~90 degree) then write quandrange
+ ## vertices to resultant sequence
+ if( s < 0.3 )
+ for i=1:4,
+ squares.append( result{i} )
+ endfor
+ endif
+ endif
+ endfor
+ endfor
+ endfor
+endfunction
+
+## the function draws all the squares in the image
+function drawSquares( img, squares )
+ global g;
+ global cv;
+
+ cpy = cvCloneImage( img );
+ ## read 4 sequence elements at a time (all vertices of a square)
+ i=0;
+ while (i<squares.total)
+ pt = { squares{i}, squares{i+1}, squares{i+2}, squares{i+3} };
+
+ ## draw the square as a closed polyline
+ cvPolyLine( cpy, {pt}, 1, CV_RGB(0,255,0), 3, cv.CV_AA, 0 );
+ i+=4;
+ endwhile
+
+ ## show the resultant image
+ cvShowImage( g.wndname, cpy );
+endfunction
+
+function on_trackbar( a )
+ global g;
+
+ if( swig_this(g.img) )
+ drawSquares( g.img, findSquares4( g.img, g.storage ) );
+ endif
+endfunction
+
+g.names = {"../c/pic1.png", "../c/pic2.png", "../c/pic3.png", \
+ "../c/pic4.png", "../c/pic5.png", "../c/pic6.png" };
+
+## create memory storage that will contain all the dynamic data
+g.storage = cvCreateMemStorage(0);
+for name = g.names,
+ g.img0 = cvLoadImage( name, 1 );
+ if (!swig_this(g.img0))
+ printf("Couldn't load %s\n",name);
+ continue;
+ endif
+ g.img = cvCloneImage( g.img0 );
+ ## create window and a trackbar (slider) with parent "image" and set callback
+ ## (the slider regulates upper threshold, passed to Canny edge detector)
+ cvNamedWindow( g.wndname, 1 );
+ cvCreateTrackbar( "canny thresh", g.wndname, g.thresh, 1000, @on_trackbar );
+ ## force the image processing
+ on_trackbar(0);
+ ## wait for key.
+ ## Also the function cvWaitKey takes care of event processing
+ c = cvWaitKey(0);
+ ## clear memory storage - reset free space position
+ cvClearMemStorage( g.storage );
+ if( c == '\x1b' )
+ break;
+ endif
+endfor
+cvDestroyWindow( g.wndname );
+
projects / opencv / blobdiff