Description: Edge detection is one of the most commonly used operations in image analysis, and
there are probably more algorithms in the literature for enhancing and detecting edges
than any other single subject. The reason for this is that edges form the outline of an
object. An edge is the boundary between an object and the background, and indicates
the boundary between overlapping objects. This means that if the edges in an image can
be identified accurately, all of the objects can be located and basic properties such as
area, perimeter, and shape can be measured. Since computer vision involves the
identification and classification of objects in an image, edge detections is an essential
tool. In this paper, we have compared several techniques for edge detection in image
processing. We consider various well-known measuring metrics used in image
processing applied to standard images in this comparison
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