Abstract
In this work, image segmentation is addressed as the starting point within a motion analysis methodology intended for rat biomechanics behavior characterization. First, we propose a general segmentation framework that uses interval valued fuzzy sets (IVFSs) to determine the optimal image threshold value. The amplitude values of the IVFSs are used for representing the unknowledge/ignorance of an expert on determining whether a pixel belongs to the background or to the object of the image. Then, we introduce an extension of this methodology that uses a heuristic-based multi-threshold approach to determine the optimal threshold. Experimental results are presented.
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Couto, P., Jurio, A., Varejão, A. et al. An IVFS-based image segmentation methodology for rat gait analysis. Soft Comput 15, 1937–1944 (2011). https://doi.org/10.1007/s00500-010-0626-7
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DOI: https://doi.org/10.1007/s00500-010-0626-7