Learning OpenCV, 2nd Edition

8

Contours

Although algorithms like the Canny edge detector can be used to find the edge pixels that separate different

segments in an image, they do not tell you anything about those edges as entities in themselves. The next

step is to be able to assemble those edge pixels into contours. By now you have probably come to expect

that there is a convenient function in OpenCV that will do exactly this for you, and indeed there is:

cv::findContours(). We will start out this chapter with some basics that we will need in order to use

this function.. With those concepts in hand, we will get into contour finding in some detail. Thereafter, we

will move on to the many things we can do with contours after they’ve been computed.

Contour Finding

A contour is a list of points that represent, in one way or another, a curve in an image. This representation

can be different depending on the circumstance at hand. There are many ways to represent a curve.

Contours are represented in OpenCV by STL style vector<> template objects in which every entry in the

vector encodes information about the location of the next point on the curve. It should be noted that though

a sequence of 2d points (vector<cv::Point> or vector<cv::Point2f>) is the most common

representation, there are other ways to represent contours as well. One example of such a construct is the

Freeman Chain, in which each point is represent ...