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Multiscale skeletons by image foresting transform and its application to neuromorphometry

✍ Scribed by A.X. Falcão; L. da Fontoura Costa; B.S. da Cunha

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
485 KB
Volume
35
Category
Article
ISSN
0031-3203

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✦ Synopsis

The image foresting transform (IFT) reduces optimal image partition problems based on seed pixels to a shortest-path forest problem in a graph, whose solution can be obtained in linear time. Such a strategy has allowed a uniÿed and e cient approach to the design of image processing operators, such as edge tracking, region growing, watershed transforms, distance transforms, and connected ÿlters. This paper presents a fast and simple method based on the IFT to compute multiscale skeletons and shape reconstructions without border shifting. The method also generates one-pixel-wide connected skeletons and the skeleton by in uence zones, simultaneously, for objects of arbitrary topologies. The results of the work are illustrated with respect to skeleton quality, execution time, and its application to neuromorphometry.

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