Conference proceeding
Reconstructing Archeological Vessels by Fusing Surface Markings and Border Anchor Points on Fragments
NEW TRENDS IN IMAGE ANALYSIS AND PROCESSING - ICIAP 2013, v 8158, pp 179-187
01 Jan 2013
Abstract
This paper presents a method to assist in the tedious process of reconstructing ceramic vessels from excavated fragments. The method exploits vessel surface marking information (models) supplied by the archaeologists along with anchor points on the fragment borders for reconstruction. Marking models are based on expert historical knowledge of the period, provenance of the artifact, and site location. The models need not to be identical to the original vessel, but must be within a geometric transformation of it in most of its parts. Marking matching is based on discrete weighted moments. We use anchor points on the fragment borders for the fragments with no markings. Corresponding anchors on different fragments are identified using absolute invariants, from which a rigid transformation is computed allowing the fragments to be virtually mended. For axially symmetric objects, a global constraint induced by the surface of revolution is applied to guarantee global mending consistency.
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Details
- Title
- Reconstructing Archeological Vessels by Fusing Surface Markings and Border Anchor Points on Fragments
- Creators
- Fernand Cohen - Drexel UniversityZexi Liu - Drexel UniversityZhongchuan Zhang - Drexel University
- Contributors
- A Petrosino (Editor)L Maddalena (Editor)P Pala (Editor)
- Publication Details
- NEW TRENDS IN IMAGE ANALYSIS AND PROCESSING - ICIAP 2013, v 8158, pp 179-187
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 9
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000343084300020
- Scopus ID
- 2-s2.0-84887033989
- Other Identifier
- 991019170615104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering
- Computer Science, Theory & Methods