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Если крут в С++, то библиотека с исходниками OpenCV

Contour Retrieving Algorithm

Four variations of algorithms described in [Suzuki85] are used in the library to retrieve
borders.
1. The first algorithm finds only the extreme outer contours in the image and
returns them linked to the list. Figure 3-2 shows these external boundaries of
W1, W2,andW3 domains.
2. The second algorithm returns all contours linked to the list. Figure 3-2 shows
the total of 8 such contours.
3. The third algorithm finds all connected components by building a two-level
hierarchical structure: on the top are the external boundaries of 1-domains and
every external boundary contains a link to the list of holes of the
corresponding component. The third algorithm returns all the connected
components as a two-level hierarchical structure: on the top are the external
boundaries of 1-domains and every external boundary contour header contains
a link to the list of holes in the corresponding component. The list can be
accessed via v_next field of the external contour header. Figure 3-2 shows
that W2, W5,andW6 domains have no holes; consequently, their boundary
contour headers refer to empty lists of hole contours. W1 domain has two holes
- the external boundary contour of W1 refers to a list of two hole contours.
Finally, W3 external boundary contour refers to a list of the single hole
contour.
4. The fourth algorithm returns the complete hierarchical tree where all the
contours contain a list of contours surrounded by the contour directly, that is,
the hole contour of W3 domain has two children: external boundary contours
of W5 and W6 domains.
All algorithms make a single pass through the image; there are, however, rare
instances when some contours need to be scanned more than once. The algorithms do
line-by-line scanning.
Whenever an algorithm finds a point that belongs to a new border the border following
procedure is applied to retrieve and store the border in the chain format. During the
border following procedure the algorithms mark the visited pixels with special positive
or negative values. If the right neighbor of the considered border point is a 0-pixel and,
at the same time, the 0-pixel is located in the right hand part of the border, the border
point is marked with a negative value. Otherwise, the point is marked with the same
magnitude but of positive value, if the point has not been visited yet. This can be easily
determined since the border can cross itself or tangent other borders. The first and
second algorithms mark all the contours with the same value and the third and fourth
algorithms try to use a unique ID for each contour, which can be used to detect the
parent of any newly met border.
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Вы имеете право хранить молчание! Всё что Вы скажете может быть использовано против Вас в суде!

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Вы имеете право хранить молчание! Всё что Вы скажете может быть использовано против Вас в суде!

Void6662 Petro123
Спасибо, помогло, кстати вот тоже неплохая ссылка с демонстрациями
http://www.cs.mcgill.ca/~aghnei/square.html
:)
Что реально работает? Быстро ты... там непростой код.