DocumentCode :
1743051
Title :
Improvement of Perez and Vidal algorithm for the decomposition of digitized curves into line segments
Author :
Salotti, Marc
Author_Institution :
Vision & Image Anal. Group, Lab. Univ. des Sci. Appliquees de Cherbourg, France
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
878
Abstract :
Perez and Vidal proposed (1994) an optimal algorithm for the decomposition of digitized curves into line segments. The number of segments is fixed a priori, and the error criterion is the sum of the square Euclidean distance from each point of the contour to its orthogonal projection onto the corresponding line segment. The complexity of Perez and Vidal algorithm is O(n2.m) where n is the number of points and m is the number of segments. We propose improvements of the algorithm to reduce the complexity, using the A* algorithm. The optimality of the algorithm is preserved and its complexity is lower. Some comparative results are presented, showing that our method is systematically faster, in particular for a large number of segments
Keywords :
computational complexity; image recognition; optimisation; A* algorithm; complexity; digitized curve decomposition; error criterion; line segments; optimal algorithm; sum of square Euclidean distance; Aggregates; Approximation algorithms; Approximation methods; Dynamic programming; Euclidean distance; Hopfield neural networks; Image edge detection; Image segmentation; Proposals; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.906214
Filename :
906214
Link To Document :
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