Abstract
In the paper we show that active contour methods can be interpreted as knowledge discovery methods. Application area is not restricted only to image segmentation, but it covers also classification of any other objects, even objects of higher granulation. Additional power of the presented method is that expert knowledge of almost any type can be used to classifier construction, which is not always possible in case of classic techniques. Moreover, the method introduced by the authors, earlier used only for supervised classification, is here applied in an unsupervised case (clustering) and examined on examples.
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Tomczyk, A., Szczepaniak, P.S., Pryczek, M. (2007). Active Contours as Knowledge Discovery Methods. In: Corruble, V., Takeda, M., Suzuki, E. (eds) Discovery Science. DS 2007. Lecture Notes in Computer Science(), vol 4755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75488-6_20
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DOI: https://doi.org/10.1007/978-3-540-75488-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75487-9
Online ISBN: 978-3-540-75488-6
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