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Unformatted text preview: segmented image must then be subjected to further processing, and the final
image segmentation may be found with the help of higher level information. Totally correct and complete segmentation of complex scenes usually cannot be achieved in
this processing phase, although substantial reduction in data volume offers an immediate
gain. A reasonable aim is to use partial segmentation as an input to higher level processing. Faculty of Engineering Robotics Technology MECH 4041 4
B.Eng (Hons.) Mechatronics S. Venkannah Mechanical and Production Engineering Department Image data ambiguity is one of the main segmentation problems, often accompanied by
In the simplest case, an image may consist of a single object or several separated objects of
relatively high intensity, viewed against a background of relatively low intensity. This allows
figure/ground separation by thresholding. In order to create the two-valued binary image a
simple threshold may be applied so that all the pixels in the image plane are classified into object
and background pixels. A binary image function can then be constructed such that pixels above
the threshold are foreground (``1'') and below the threshold are background (``0''). The simplest type of image which is used widely in a variety of industrial and medical
applications is binary, i.e. a black-and-white or silhouette image. Binary image processing has
several advantages but some corresponding drawbacks:
• Easy to acquire: simple digital cameras can be used together with very simple
framestores, or low-cost scanners, or thresholding may be applied to gray-level images.
Low storage: no more than 1 bit/pixel, often this can be reduced.
Simple processing: the algorithms are in most cases much simpler than those applied to
gray-level images. Disadvantages
• Limited application: as the representation is only a silhouette
Does not extend to 3D: the 3D nature of objects can rarely be represented by silhouettes.
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- Spring '14