DocumentCode :
2467712
Title :
The optimal implementation of morphological operations on neighborhood connected array processors
Author :
Xu Jianning
Author_Institution :
Dept. of Math. & Comput. Sci., Classboro State Coll., NJ
fYear :
1989
fDate :
4-8 Jun 1989
Firstpage :
166
Lastpage :
171
Abstract :
Neighborhood-connected array processors can implement Minkowski addition and Minkowski subtraction operations with structuring elements larger than the neighborhood size by breaking the operation into a sequence of successive neighborhood operations. The author provides a complete solution to the problem of decomposing convex polygons into subsets of the 3×3 neighborhood set. With the help of the Freeman chain code notation, it is proved that all convex polygons have neighborhood decompositions. Based on this result, an efficient algorithm is developed which can find an optimal decomposition for any convex polygon. The decomposition produced by the algorithm can be used to determine the most efficient implementation of a morphological operation with convex polygonal structuring elements as a sequence of successive neighborhood operations. Therefore, the algorithm is applicable to neighborhood-connected array processors, or any machine structure that can quickly perform 3×3 neighborhood operations
Keywords :
codes; computerised picture processing; set theory; Freeman chain code; Minkowski addition; Minkowski subtraction; computerised picture processing; convex polygons; decompositions; morphology; neighborhood connected array processors; set theory; Arithmetic; Computer science; Educational institutions; Image analysis; Image sequence analysis; Logic; Mathematics; Morphological operations; Morphology; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on
Conference_Location :
San Diego, CA
ISSN :
1063-6919
Print_ISBN :
0-8186-1952-x
Type :
conf
DOI :
10.1109/CVPR.1989.37845
Filename :
37845
Link To Document :
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