Authors:
Gianfranco Fenu
1
;
Nikita Jain
2
;
Eric Medvet
1
;
Felice Andrea Pellegrino
1
and
Myriam Pilutti Namer
3
Affiliations:
1
University of Trieste, Italy
;
2
Delhi Technological University, India
;
3
Ca' Foscari University of Venice, Italy
Keyword(s):
Image Segmentation, Superpixel, Comparative Evaluation, Cultural Heritage Preservation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Imaging for Cultural Heritage (Modeling/Simulation, Virtual Restoration)
;
Segmentation and Grouping
Abstract:
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.