Hand detection using contour method

Contours can be explained simply as a curve joining all the continuous points (along the boundary), having same color or intensity. The contours are a useful tool for shape analysis and object detection and recognition.

There are 3 flags under cv2.findContours()┬ácategory, but I am discussing only the first two – cv2.CHAIN_APPROX_NONE and cv2.CHAIN_APPROX_SIMPLE.

First one finds all the points on the contour or the boundary. But actually do we need all the points? For e.g. , you found the contour of a straight line. Do you need all the points on the line to represent that line? No, we need just two end points of that line. This is what second flag does. It removes all redundant points and compresses the contour.

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Hand detection (using skin tone)

Hand detection using skin tone is the simplest way to detect hand. Problems of this method are the background should not contain skin colored, really sensitive to light and shape of background!

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