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Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12128/3464
Title: Recognition of Two-dimensional Shapes Based on Dependence Vectors
Authors: Gdawiec, Krzysztof
Domańska, Diana
Keywords: fractals; dependence vectors; pattern recognition
Issue Date: 2012
Publisher: Springer
Citation: Lecture Notes in Artificial Intelligence, vol. 7267, pp. 501-508, (2012)
Abstract: The aim of this paper is to present a new method of two-dimensional shape recognition. The method is based on dependence vectors which are fractal features extracted from the partitioned iterated function system. The dependence vectors show the dependency between range blocks used in the fractal compression. The effectiveness of our method is shown on four test databases. The first database was created by the authors and the other ones are: MPEG7 CE-Shape-1PartB, Kimia-99, Kimia-216. Obtained results have shown that the proposed method is better than the other fractal recognition methods of two-dimensional shapes.
URI: http://hdl.handle.net/20.500.12128/3464
DOI: 10.1007/978-3-642-29347-4_58
ISBN: 978-3-642-29346-7
ISSN: 0302-9743
Appears in Collections:Materiały konferencyjne (WNŚiT)

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