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- Title
A New Concave Hull Algorithm and Concaveness Measure for n-dimensional Datasets.
- Authors
JIN-SEO PARK; SE-JONG OH
- Abstract
Convex and concave hulls are useful concepts for a wide variety of application areas, such as pattern recognition, image processing, statistics, and classification tasks. Concave hull performs better than convex hull, but it is difficult to formulate and few algorithms are suggested. Especially, an n-dimensional concave hull is more difficult than a 2- or 3-dimensional one. In this paper, we propose a new concave hull algorithm for n-dimensional datasets. It is simple but creative. We show its application to dataset analysis. We also suggest a concaveness measure and a graph that captures geometric shape of an n-dimensional dataset. Proposed concave hull algorithm and concaveness measure/graph are implemented using java, and are posted to http://user.dankook.ac.kr/ ~bitl/dkuCH.
- Subjects
COMPUTER algorithms; DATABASES; PATTERN recognition systems; IMAGE processing; STATISTICS; JAVA programming language; COMPUTATIONAL complexity
- Publication
Journal of Information Science & Engineering, 2013, Vol 29, Issue 2, p379
- ISSN
1016-2364
- Publication type
Article