Paper Info
Title
A novel split-and-merge technique for error-bounded polygonal approximation
Abstract
How to use a polygon with the fewest possible sides to approximate a shape boundary is an important issue in pattern recognition and image processing. A novel split-and-merge technique(SMT) is proposed. SMT starts with an initial shape boundary segmentation, split and merge are then alternately done against the shape boundary. The procedure is halted when the pre-specified iteration number is achieved. For increasing stability of SMT and improving its robustness to the initial segmentation, a ranking-selection scheme is utilized to choose the splitting and merging points. The experimental results show its superiority.
Year
DOI
Venue
2006
10.1007/11893257_37
ICONIP
Keywords
Field
DocType
important issue,fewest possible side,pre-specified iteration number,pattern recognition,novel split-and-merge technique,shape boundary,error-bounded polygonal approximation,image processing,initial shape boundary segmentation,initial segmentation
Polygon,Computer science,Segmentation,Concurrency,Algorithm,Image processing,Robustness (computer science),Artificial neural network,Approximation error,Bounded function
Conference
Volume
ISSN
ISBN
4233
0302-9743
3-540-46481-6
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Bin Wang132130.75
Chaojian Shi2246.74