Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/7219
Title: Knowledge-based image segmentation
Authors: Kasparis, Takis 
Marinovic, Nenad M.
Eichmann, George 
Keywords: Image processing
Pattern recognition
Computer vision
Issue Date: 1987
Publisher: SPIE
Source: Intelligent Robots and Computer Vision: Fifth in a Series, 1987, Cambridge, England
Abstract: Image segmentation is a highly scene dependent and problem dependent decision making or pattern recognition process. Knowledge about the class of images to be processed and the tasks to be performed plays an important role. Two approaches that explicitly incorporate such knowledge are advanced for the class of images containing polygonal shapes. They can be generalized to other shapes by change of preprocessing steps. Inference is both data driven and goal driven. It is guided by meta rules that are fired by the outputs of preprocessing. Effective suppression of noise is achieved. The methods illustrate the potential of AI techniques and tools for low-level image understanding tasks.
URI: http://ktisis.cut.ac.cy/handle/10488/7219
ISSN: 0277786X
DOI: 10.1117/12.937741
Rights: © 1987 SPIE
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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