On the Assessment of Segmentation Methods for Images of Mosaics

posted Dec 5, 2014, 5:32 AM by Eric Medvet   [ updated Mar 25, 2015, 9:01 AM ]
  • 10th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2015, Berlin (Germany)
  • Gianfranco Fenu, Nikita Jain, Eric Medvet, Felice Andrea Pellegrino, Myriam Pilutti Namer
  • Google Scholar
The present paper deals with automatic segmentation of mosaics, whose aim is obtaining a digital representation of the mosaic where the shape of each tile is recovered. This is an important step, for instance, for preserving ancient mosaics. By using a ground-truth consisting of a set of manually annotated mosaics, we objectively compare the performance of some existing recent segmentation methods, based on a simple error metric taking into account precision, recall and the error on the number of tiles. Moreover, we introduce some mosaic-specific hardness estimators (namely some indexes of how difficult is the task of segmenting a particular mosaic image). The results show that the only segmentation algorithm specifically designed for mosaics performs better than the general purpose algorithms. However, the problem of segmentation of mosaics appears still partially unresolved and further work is needed for exploiting the specificity of mosaics in designing new segmentation algorithms.
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Eric Medvet,
Mar 25, 2015, 9:03 AM