DocumentCode :
2039646
Title :
Strategy for shape-based image analysis
Author :
Reinhardt, Joseph M. ; Higgins, William E.
Author_Institution :
Coll. of Med., Iowa Univ., Iowa City, IA, USA
Volume :
1
fYear :
1995
fDate :
23-26 Oct 1995
Firstpage :
502
Abstract :
Traditional image segmentation methods typically divide an image into separate regions based on the grayscale characteristics of the image. For most real-world image-segmentation problems, however, these methods tend to produce imperfectly shaped regions that require some degree of shape modification to yield acceptable results. Choosing an appropriate sequence of operators and associated operator parameters, though, is a tedious procedure and requires much image-processing expertise. We describe a strategy for easily selecting shape-based operations. Shape information on regions in an image is provided by the user in the form of easily-specified cues. The user is not required to be an image-processing expert to apply the strategy-he need only be able to specify the desired shape properties of the regions in the image
Keywords :
image segmentation; grayscale characteristics; image processing; image regions; image segmentation methods; operator parameters; shape based image analysis; shape based operation selection; shape information; shape modification; shape properties; Biomedical imaging; Cities and towns; Educational institutions; Gray-scale; Image analysis; Image segmentation; Image sequence analysis; Radiology; Shape; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1995. Proceedings., International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-7310-9
Type :
conf
DOI :
10.1109/ICIP.1995.529756
Filename :
529756
Link To Document :
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