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#X text 26 175 Arguments:;
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#X text 22 38 Class: pix_opencv;
#X text 23 22 Synopsis: [pix_opencv_calibration];
#X text 47 195 none;
#X text 26 86 pix_opencv_contours_convexity :: Finds convexity defects
of the bigest contour of a binary image.;
#X text 25 228 This object considers a contour to be analyzed any group
of white pixels in a black background \, for this reason you will find
useful to use pix_threshold to obtain a correct input for pix_opencv_contours_boundingrect.
;
#X text 26 281 pix_opencv_contours_boundingrect works detecting the
bigest white area in the input image \, sometimes you will need to
use pix_opencv_morphology to transform the contours of the shape to
be analyzed..;
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#X obj 635 199 pix_film;
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#X text 840 246 Create window and render;
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#X text 819 589 Start point (X -Y);
#X text 883 569 Depth point (X -Y);
#X text 948 551 End point (X -Y);
#X floatatom 694 441 5 0 0 0 - - -;
#X text 730 445 number convexity defects in our detected contour;
#X text 692 484 A convexity defect is defined by 3 points. So for each
convexity defects we have ::;
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#X obj 609 421 pix_opencv_contours_convexity;
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#X msg 623 348 set;
#X text 652 347 <- Set the background reference;
#X text 790 369 <-Adjust threshold;
#X text 796 389 <-Adjust morphology if needed;
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#X text 74 445 please consider the use of pix_opencv_contours;
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