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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/45833
Title: An Automatic Pruning Method for Skeleton Images
Authors: Jun Ma
Xunhuan Ren
Konopelko, V.
Tsviatkou, V. Y.
Конопелько, В. К.
Цветков, В. Ю.
Keywords: материалы конференций;conference proceedings;skeleton;automatic skeleton pruning;skeletonization
Issue Date: 2021
Publisher: UIIP NASB
Citation: An Automatic Pruning Method for Skeleton Images / Jun Ma [et al.] // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 232–235.
Abstract: Skeletons can be regarded as a compact shape representation in that each pattern can be completely reconstructed from its skeleton. One of the limitations of the application of the skeleton for object analysis and recognition is the existence of redundant skeleton branches. Skeleton pruning is an effective way to remove the redundant skeleton branches in the skeleton images. However, most of the existing pruning methods require manual tuning of the parameter to control the power of pruning, which is not convenient to use. In this paper, we have proposed a fully automatic pruning method that adjusts the power of the pruning according to the image and achieves good pruning results in the experiment.
URI: https://libeldoc.bsuir.by/handle/123456789/45833
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)

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