Abstract
In this paper we revisit the Mumford-Shah functional, one of the most studied variational approaches to image segmentation. The contribution of this work is to propose a modification of the Mumford-Shah functional that includes Fractal Analysis to improve the segmentation of images with fractal or semi-fractal objects. Here we show how the fractal dimension is calculated and embedded in the functional minimization computation to drive the algorithm to use both, changes in the image intensities and the fractal characteristics of the objects, to obtain a more suitable segmentation. Experimental results confirm that the proposed modification improves the quality of the segmentation in images with fractal objects or semi fractal such as medical images.
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Guillén Galván, C., Valdés Amaro, D., Uriarte Adrián, J. (2011). A Modification of the Mumford-Shah Functional for Segmentation of Digital Images with Fractal Objects. In: Batyrshin, I., Sidorov, G. (eds) Advances in Soft Computing. MICAI 2011. Lecture Notes in Computer Science(), vol 7095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25330-0_41
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DOI: https://doi.org/10.1007/978-3-642-25330-0_41
Publisher Name: Springer, Berlin, Heidelberg
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