Lecture #13 Edge Detection

Digital Image Processing lec.(13) 4th class
Edge Detection
De?nition of edges
• Edges are signi?cant local changes of intensity in an image.
• Edges typically occur on the boundary between two different regions in an image.
Detecting edges is a basic operation in image processing. The edges of items in an image hold much of the information in the image.
Goal of edge detection
• Produce a line drawing of a scene from an image of that scene.
• Important features can be extracted from the edges of an image (e.g., corners, lines, curves).
• These features are used by higher-level computer vision algorithms (e.g., recognition).



What causes intensity changes?
Various physical events cause intensity changes.
1-Geometric events
*object boundary (discontinuity in depth and/or surface color and texture)
*surface boundary (discontinuity in surface orientation and/or surface color and texture)
2-Non-geometric events
*specularity (direct re?ection of light, such as a mirror)
*shadows (from other objects or from the same object)
*inter-re?ections
Edge detection methods are used as a first step in the line detection
processes, and they are used to find object boundaries by marking potential edge points corresponding to place in an image where rapid changes in brightness occur. After these edge points have been marked, they can be merged to form lines and objects outlines.
Edge detection operations are based on the idea that edge information in an image is found by looking at the relationship a pixel has with its neighbors. If a pixel gray_level values similar to those around it, there is probably not an edge at that point at that point. However, if a pixel has neighbors with widely varying gray levels, it may represent an edge point. In other words, an edge is defined by a discontinuity in gray-level values. Ideally, an ege separates two distinct objects.
The following figure illustrates the difference between an ideal edge and a real edge.



The vertical axis represents brightness, and the horizontal axis shows the
spatial coordinates. The abrupt change in brightness characterizes an ideal
edge. In the figure (b) we see the representation of real edge ,which change gradually.

Edge detection using the gradient
-The gradient is a vector which has certain magnitude and direction:


-To save computations, the magnitude of gradient is usually approximated by