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Image and pattern analysis of 1650 B.C. wall paintings and reconstruction
- Source :
- IEEE Transactions on Systems, Man, and Cybernetics--Part A: Systems and Humans. July, 2008, Vol. 38 Issue 4, p958, 8 p.
- Publication Year :
- 2008
-
Abstract
- In this paper, a color image segmentation method and a pattern analysis are presented, in connection with the extraordinary 1650 B.C. wall paintings found in the Greek island of Thera. These wall paintings are usually reconstructed from thousands of fragments widely scattered in the excavated site. The fragments' depiction manifests inhomogeneous color decay, cracks, added extraneous material, etc. The proposed color image segmentation method takes into account the decay problems and offers a very good approximation of the initial fragment depiction as the artist drew it in the late Bronze Age. The algorithm performs essentially better than other standard segmentation schemes as extensive qualitative tests indicate. Moreover, it offers clear-cut color regions and region borders for each fragment depiction. The whole approach is based on classifying the pixels into a number of regions where each region is described by a normal distribution, followed by fragment-decay reduction and edge refining. Extensive pattern analysis to the obtained region borders leads to the conclusion that 3650 years ago, the artist most probably used advanced geometrical methods in order to construct handcrafted "French curves" (stencils or templates) and use them to draw certain figures. On the basis of the aforementioned results, specific pattern matching techniques are employed for the reconstruction of wall paintings, depicting spirals, from their constituent fragments. Index Terms--Curve fitting, image reconstruction, image segmentation.
- Subjects :
- Image processing -- Analysis
Subjects
Details
- Language :
- English
- ISSN :
- 10834427
- Volume :
- 38
- Issue :
- 4
- Database :
- Gale General OneFile
- Journal :
- IEEE Transactions on Systems, Man, and Cybernetics--Part A: Systems and Humans
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.181154637