Abstract
This paper presents a novel pyramid approach for fast segmentation of 3D images. A pyramid is a hierarchy of successively reduced graphs whose efficiency is strongly influenced by the data structure that codes the information within the pyramid and the decimation process used to build a graph from the graph below. Depending on these two features, pyramids have been classified as regular and irregular ones. The proposed approach extends the idea of the Bounded Irregular Pyramid (BIP) [5] to 3D images. Thus, the 3D-BIP is a mixture of both types of pyramids whose goal is to combine their advantages: the low computational cost of regular pyramids with the consistent and useful results provided by the irregular ones. Specifically, its data structure combines a regular decimation process with an union-find strategy to build the successive 3D levels of the structure. Experimental results show that this approach is able to provide a low–level segmentation of 3D images at a low computational cost.
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Torres, F., Marfil, R., Bandera, A. (2009). 3D Image Segmentation Using the Bounded Irregular Pyramid. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_119
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DOI: https://doi.org/10.1007/978-3-642-03767-2_119
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