Attribute Controlled Reconstruction and Adaptive Mathematical Morphology

Abstract : In this paper we present a reconstruction method controlled by the evolution of attributes. The process begins from a marker, propagated over increasing quasi-flat zones. The evolution of several increasing and non-increasing attributes is studied in order to select the appropriate region. Additionally, the combination of attributes can be used in a straightforward way. To demonstrate the performance of our method, three applications are presented. Firstly, our method successfully segments connected objects in range images. Secondly, input-adaptive structuring elements (SE) are defined computing the controlled propagation for each pixel on a pilot image. Finally, input-adaptive SE are used to assess shape features on the image. Our approach is multi-scale and auto-dual. Compared with other methods, it is based on a given attribute but does not require a size parameter in order to determine appropriate regions. It is useful to extract objects of a given shape. Additionally, our reconstruction is a connected operator since quasi-flat zones do not create new contours on the image.
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Cris L. Luengo Hendriks, Gunilla Borgefors, and Robin Strand. 11th International Symposium, ISMM 2013, May 2013, Uppsala, Sweden. Springer, 7883, pp.207-218, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-38294-9_18〉
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Andrés Serna, Beatriz Marcotegui. Attribute Controlled Reconstruction and Adaptive Mathematical Morphology. Cris L. Luengo Hendriks, Gunilla Borgefors, and Robin Strand. 11th International Symposium, ISMM 2013, May 2013, Uppsala, Sweden. Springer, 7883, pp.207-218, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-38294-9_18〉. 〈hal-00834638〉

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