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• W2086074953 abstract "Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method, and its results are compared to traditional shape analysis methods found in literature." @default.
• W2086074953 created "2016-06-24" @default.
• W2086074953 creator A5043350656 @default.
• W2086074953 creator A5074213486 @default.
• W2086074953 date "2010-01-01" @default.
• W2086074953 modified "2023-10-14" @default.
• W2086074953 title "Shape classification using complex network and Multi-scale Fractal Dimension" @default.
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• W2086074953 doi "https://doi.org/10.1016/j.patrec.2009.08.007" @default.
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