EconPapers    
Economics at your fingertips  
 

Data Reduction of Piecewise Linear Curves

Erlend Arge () and Morten Dæhlen ()
Additional contact information
Erlend Arge: SINTEF
Morten Dæhlen: SINTEF

Chapter 17 in Numerical Methods and Software Tools in Industrial Mathematics, 1997, pp 347-364 from Springer

Abstract: Abstract We present and study two new algorithms for data reduction or simplification of piecewise linear plane curves. Given a curve P and a tolerance ε ≥ 0, both methods determine a new curve Q, with few vertices, which is at most e in Hausdorff distance from P. The methods differ from most existing methods in that they do not require a vertex in Q to be a vertex in P. Several examples are given where we show that the methods presented here compare favorably to other methods found in the literature. We also show how the vertices of a curve can be reordered so that the first, say n, vertices of the reordered sequence form an approximation to the curve itself.

Keywords: Data Reduction; Local Algorithm; Hausdorff Distance; General Step; Point Sequence (search for similar items in EconPapers)
Date: 1997
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-1984-2_17

Ordering information: This item can be ordered from
http://www.springer.com/9781461219842

DOI: 10.1007/978-1-4612-1984-2_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-08-12
Handle: RePEc:spr:sprchp:978-1-4612-1984-2_17