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scicv >> Image analysis > findContours

findContours

Calculates the derivatives of an image

Syntax

[contours] = findContours(img_in, mode, method[, offset])

Parameters

img_in

Input image (single channel 8-bit, or 32-bit if mode is CV_RETR_CCOMP or CV_RETR_FLOODFILL) (Mat).

mode

Contour retrieval mode (double):

  • CV_RETR_EXTERNAL: returns only the outer contours.
  • CV_RETR_LIST: returns all the contours.
  • CV_CCOMP: returns a two level hierarchy in which the top level contains the outer boundaries of components, and the second level contains the holes.
  • CV_RETR_TREE: returns full hierarchy of contours.
method

Contour approximation method (double).

  • CV_CHAIN_APPROX_ONE: stores all the contour points.
  • CV_RETR_LIST: stores only end points of (horizontal/vertical/diagonal) segments.
  • CV_CHAIN_APPROX_TC89_L1, CV_CHAIN_APPROX_TC89_KCOS: used the the Tech-Chin algorithm to store points.
offset

Optional offset by which every contour point is shifted (default [0, 0]).

contours

List of detected contours (VecPoints).

Description

findContours retrieves the contours from a binary image.

Examples

scicv_Init();

img_gray = imread(getSampleImage("shapes.png"), CV_LOAD_IMAGE_GRAYSCALE);

subplot(1,2,1);
matplot(img_gray);

thresh = 100;
img_canny = Canny(img_gray, thresh, thresh*2, 3);

[contours] = findContours(img_canny, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, [0, 0]);

subplot(1,2,2);
img_contours = new_Mat(size(img, 'c'), size(img, 'r'), CV_8UC1, 0);
img_contours_out = drawContours(img_contours, contours, -1, [255, 0, 0], -1);
matplot(img_contours_out);
title("contours");

delete_Mat(img_gray);
delete_Mat(img_canny);
delete_Mat(img_contours);

See also

History

VersionDescription
4.8.1 findContours() no more returns image.

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