DocumentCode :
1557301
Title :
Parallel image component labelling with watershed transformation
Author :
Moga, Alina N. ; Gabbouj, Moncef
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Volume :
19
Issue :
5
fYear :
1997
fDate :
5/1/1997 12:00:00 AM
Firstpage :
441
Lastpage :
450
Abstract :
The parallel watershed transformation used in gray scale image segmentation is reconsidered on the basis of the component labeling problem. The main idea is to break the sequentiality of the watershed transformation and to correctly delimit the extent of all connected components locally, on each processor, simultaneously. The internal fragmentation of the catchment basins, due to domain decomposition, into smaller subcomponents is finally solved by employing a global connected components operator. Therefore, in a pyramidal structure of master-slave processors, internal contours of adjacent subcomponents within the same component are hierarchically removed. Global final connected areas are efficiently obtained in log2 N steps on a logical grid of N processors. Timings and segmentation results of the algorithm built on top of the message passing interface and tested on the Gray T3D are brought forward to justify the superiority of the novel design solution compared against previous implementations
Keywords :
computational complexity; computer vision; image segmentation; message passing; parallel algorithms; transforms; computational complexity; domain decomposition; gray scale image; image segmentation; internal contours; internal fragmentation; message passing interface; parallel algorithm; parallel labelling; watershed transformation; Algorithm design and analysis; Concurrent computing; Image segmentation; Labeling; Message passing; Parallel processing; Pixel; Software algorithms; Testing; Timing;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.589204
Filename :
589204
Link To Document :
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