Abstract
We propose a method for interactive image segmentation. We construct a weighted graph that represents the superpixels and the connections between them. An efficient algorithm for graph clustering based on synthetic coordinates is used yielding an initial map of classified pixels. The proposed method minimizes a min-max Bayesian criterion that has been successfully used on image segmentation problem taking into account visual information as well as the given markers. Experimental results and comparisons with other methods demonstrate the high performance of the proposed scheme.
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Panagiotakis, C., Papadakis, H., Grinias, E., Komodakis, N., Fragopoulou, P., Tziritas, G. (2013). Interactive Image Segmentation via Graph Clustering and Synthetic Coordinates Modeling. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_71
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DOI: https://doi.org/10.1007/978-3-642-40261-6_71
Publisher Name: Springer, Berlin, Heidelberg
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