diplomsko delo
Jordan Lesjak (Author), Borut Robič (Mentor)

Abstract

Konveksno ovojnico množice točk v ravnini si lahko predstavljamo kot najmanjši konveksen poligon, ki obdaja celotno množico. Računanje konveksne ovojnice je v praksi pogosta operacija in ima uporabo na številnih področjih stroke. V tem diplomskem delu so predstavljeni in analizirani številni tradicionalni in moderni algoritmi za izračun konveksne ovojnice v dvodimenzionalnem Evklidskem prostoru, ki so nato ovrednoteni na podlagi različnih praktičnih performančnih testov. Bolj podrobno je predstavljen algoritem Ordered hull, ki se je izkazal za bistveno hitrejšega od algoritma Quickhull, ki je dolgo časa veljal za najhitrejšega.

Keywords

konveksna ovojnica;ravnina;algoritem;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [J. Lesjak]
UDC: 004(043.2)
COBISS: 65721091 Link will open in a new window
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Downloads: 62
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Other data

Secondary language: English
Secondary title: Overview and comparison of convex hull algorithms
Secondary abstract: The convex hull of a planar point set is the smallest convex polygon enclosing the entire set. Computing the convex hull is a fundamental operation with uses in several different fields of research. In this thesis, we explore several different traditional and modern algorithms for computing the convex hull in two dimensional Euclidean space. The algorithms are then evaluated through several different practical performance tests. Algorithm Ordered hull is described in greater detail, as it proved to be significantly faster than Quickhull, which is commonly regarded as the fastest algorithm for the problem.
Secondary keywords: convex hull;plane;algorithm;computer and information science;diploma;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 60 str.
ID: 12977412
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