DocumentCode :
831592
Title :
Efficient parallel processing of image contours
Author :
Chen, Ling Tony ; Davis, Larry S. ; Kruskal, Clyde P.
Author_Institution :
Maryland Univ., College Park, MD, USA
Volume :
15
Issue :
1
fYear :
1993
fDate :
1/1/1993 12:00:00 AM
Firstpage :
69
Lastpage :
81
Abstract :
Describes two parallel algorithms for ranking the pixels on a curve in O (log N) time using either an EREW or CREW PRAM model. The algorithms accomplish this with N processors for a √N×√N image. After applying such an algorithm to an image, it is possible to move the pixels from a curve into processors having consecutive addresses. This is important because one can subsequently apply many algorithms to the curve (such as piecewise linear approximation algorithms or point in polygon tests) using segmented scan operations (i.e. parallel prefix operations). Scan operations can be executed in logarithmic time on many interconnection networks, such as hypercube, tree, butterfly, and shuffle exchange machines as well as on the EREW PRAM. The algorithms were implemented on the hypercube structured Connection Machine, and various performance tests were conducted
Keywords :
computational complexity; computer vision; hypercube networks; image processing; parallel algorithms; parallel processing; CREW PRAM model; Connection Machine; EREW model; computer vision; hypercube; image contours; parallel algorithms; parallel processing; segmented scan operations; Approximation algorithms; Hypercubes; Image segmentation; Multiprocessor interconnection networks; Parallel algorithms; Parallel processing; Phase change random access memory; Piecewise linear approximation; Pixel; Testing;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.184775
Filename :
184775
Link To Document :
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