DocumentCode :
1456640
Title :
Image segmentation and analysis via multiscale gradient watershed hierarchies
Author :
Gauch, John M.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Kansas Univ., Lawrence, KS, USA
Volume :
8
Issue :
1
fYear :
1999
fDate :
1/1/1999 12:00:00 AM
Firstpage :
69
Lastpage :
79
Abstract :
Multiscale image analysis has been used successfully in a number of applications to classify image features according to their relative scales. As a consequence, much has been learned about the scale-space behavior of intensity extrema, edges, intensity ridges, and grey-level blobs. We investigate the multiscale behavior of gradient watershed regions. These regions are defined in terms of the gradient properties of the gradient magnitude of the original image. Boundaries of gradient watershed regions correspond to the edges of objects in an image. Multiscale analysis of intensity minima in the gradient magnitude image provides a mechanism for imposing a scale-based hierarchy on the watersheds associated with these minima. This hierarchy can be used to label watershed boundaries according to their scale. This provides valuable insight into the multiscale properties of edges in an image without following these curves through scale-space. In addition, the gradient watershed region hierarchy can be used for automatic or interactive image segmentation. By selecting subtrees of the region hierarchy, visually sensible objects in an image can be easily constructed
Keywords :
feature extraction; image classification; image segmentation; Gaussian filtering; automatic image segmentation; edges; gradient magnitude; gradient watershed regions; grey-level blobs; image feature classification; intensity extrema; intensity minima; intensity ridges; interactive image segmentation; multiscale gradient watershed hierarchies; multiscale image analysis; scale-space behavior; subtrees; watershed boundaries; Application software; Computer vision; Image analysis; Image edge detection; Image resolution; Image segmentation; Performance evaluation; Position measurement; Shape measurement; Signal resolution;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.736688
Filename :
736688
Link To Document :
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