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Image segmentation
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== Semi-automatic segmentation == In one kind of segmentation, the user outlines the region of interest with the mouse clicks and algorithms are applied so that the path that best fits the edge of the image is shown. Techniques like [[Simple Interactive Object Extraction|SIOX]], [[Livewire Segmentation Technique|Livewire]], Intelligent Scissors or IT-SNAPS are used in this kind of segmentation. In an alternative kind of semi-automatic segmentation, the algorithms return a spatial-taxon (i.e. foreground, object-group, object or object-part) selected by the user or designated via prior probabilities.<ref>Barghout, Lauren. Visual Taxometric Approach to Image Segmentation using Fuzzy-Spatial Taxon Cut Yields Contextually Relevant Regions. IPMU 2014, Part II. A. Laurent et al (Eds.) CCIS 443, pp 163β173. Springer International Publishing Switzerland</ref><ref>{{cite book|last1=Barghout|first1=Lauren|title=Vision: How Global Perceptual Context Changes Local Contrast Processing (Ph.D. Dissertation 2003). Updated to include Computer Vision Techniques|date=2014|publisher=Scholars Press|isbn=978-3-639-70962-9|url=https://www.morebooks.de/store/gb/book/vision/isbn/978-3-639-70962-9}}</ref>
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