Abstract
The image foresting transform (IFT) can divide an image into object and background, each represented by one optimum-path forest rooted at internal and external markers selected by the user. We have considerably reduced the number of markers (user involvement) by separating object enhancement from its extraction. However, the user had no guidance about effective marker location during extraction, losing segmentation control. Now, we pre-segment the image automatically into a few regions. The regions inside the object are selected and merged from internal markers. Regions with object and background pixels are further divided by IFT. This provides more user control with minimum involvement, as validated on two public datasets.
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Spina, T.V., Montoya-Zegarra, J.A., Miranda, P.A.V., Falcão, A.X. (2009). Improving User Control with Minimum Involvement in User-Guided Segmentation by Image Foresting Transform. 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_118
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DOI: https://doi.org/10.1007/978-3-642-03767-2_118
Publisher Name: Springer, Berlin, Heidelberg
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