Image-Based Retrieval and Identification of Ancient Coins

Martin Kampel; Reinhold Huber-M&#x00F6;rk; Maia Zaharieva

doi:10.1109/MIS.2009.29

Intelligent Systems
2009
Issue No. 2 - March/April
Abstract - Image-Based Retrieval and Identification of Ancient Coins

	This Article
	Subscribers, please Login Purchase article: $19 PDF HTML IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/EndNote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Martin Kampel Articles by Reinhold Huber-Mörk Articles by Maia Zaharieva

Image-Based Retrieval and Identification of Ancient Coins

March/April 2009 (vol. 24 no. 2)

pp. 26-34

	ASCII Text	x
	Martin Kampel, Reinhold Huber-Mörk, Maia Zaharieva, "Image-Based Retrieval and Identification of Ancient Coins," IEEE Intelligent Systems, vol. 24, no. 2, pp. 26-34, March/April, 2009.

	BibTex	x
	@article{ 10.1109/MIS.2009.29, author = {Martin Kampel and Reinhold Huber-Mörk and Maia Zaharieva}, title = {Image-Based Retrieval and Identification of Ancient Coins}, journal ={IEEE Intelligent Systems}, volume = {24}, number = {2}, issn = {1541-1672}, year = {2009}, pages = {26-34}, doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2009.29}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - MGZN JO - IEEE Intelligent Systems TI - Image-Based Retrieval and Identification of Ancient Coins IS - 2 SN - 1541-1672 SP26 EP34 EPD - 26-34 A1 - Martin Kampel, A1 - Reinhold Huber-Mörk, A1 - Maia Zaharieva, PY - 2009 KW - object identification KW - shape descriptors KW - local features KW - coin identification VL - 24 JA - IEEE Intelligent Systems ER -

Martin Kampel, Vienna University of Technology

Reinhold Huber-Mörk, Austrian Research Centers

Maia Zaharieva, Vienna University of Technology

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2009.29

Reliable object identification is an essential task in the process of recognizing and tracing stolen cultural heritage. We investigate the feasibility of using computer-aided identification of ancient coins to search for a given coin on the Internet or in a digital repository. Because a coin's shape is a unique feature, we first apply a shape descriptor to capture its characteristics. Then, we use local features to describe the die information. The approach presented here shows promise for reliably identifying objects in the area of cultural heritage.

1. M. Zaharieva et al., "On Ancient Coin Classification," Proc. Int'l Symp. Virtual Reality, Archaeology and Cultural Heritage (VAST 07), Transatlantic Publishers Group, 2007, pp. 55–62.
2. D. Iakovidis et al., "Pattern-Based Retrieval of Cultural Heritage Images," Current Trends in Informatics, vol. A, Proc. 11th Panhellenic Conf. Informatics, New Technologies Publications, 2007, pp. 443–452.
3. R. Veltkamp and M. Tanase, Content-Based Image Retrieval Systems: A Survey, tech. report UU-CS-2000-34, Dept. of Computing Science, Utrecht Univ., 2000.
4. E. Saber and A.M. Tekalp, "Integration of Color, Edge, Shape and Texture Features for Automatic Region-Based Image Annotation and Retrieval," Electronic Imaging, vol. 7, 1998, pp. 684–700.
5. A. Bosch, X. Muñoz, and R. Marti, "A Review: Which Is the Best Way to Organize/Classify Images by Content?" Image and Vision Computing, vol. 25, no. 6, 2007, pp. 778–791.
6. R.C. Veltkamp, Shape Matching: Similarity Measures and Algorithms, tech. report UU-CS 2001-03, Information and Computing Sciences Dept., Utrecht Univ., 2001.
7. J. Ruisz, J. Biber, and M. Loipetsberger, "Quality Evaluation in Resistance Spot Welding by Analysing the Weld Fingerprint on Metal Bands by Computer Vision," Int'l J. Advanced Manufacturing Technology, vol. 33, nos. 9–10, 2007, pp. 952–960.
8. S. Zambanini and M. Kampel, "Segmentation of Ancient Coins Based on Local Entropy and Gray Value Range," Proc. 13th Computer Vision Winter Workshop, Vienna Univ. of Technology, 2008, pp. 9–16.
9. M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine Vision, 2nd ed., Brooks and Cole Publishing, 1998.
10. S. Lazebnik, C. Schmid, and J. Ponce, "A Sparse Texture Representation Using Local Affine Regions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 8, 2005, pp. 1265–1799.
11. D.G. Lowe, "Distinctive Image Features from Scale Invariant Keypoints," Int'l J. Computer Vision, vol. 60, no. 2, 2004, pp. 91–110.
12. H. Bay, T. Tuytelaars, and L.V. Gool, "SURF: Speeded Up Robust Features," European Conf. Computer Vision, LNCS 3951, Springer, 2006, pp. 404–417.
13. A. Felicetti, "MAD—Management of Archaeological Data," The E-volution of Information Communication Technology in Cultural Heritage, M. Ioannides et al., eds., Archaeolingua, 2006, pp. 124–131.

Index Terms:

object identification, shape descriptors, local features, coin identification

Citation:

Martin Kampel, Reinhold Huber-Mörk, Maia Zaharieva, "Image-Based Retrieval and Identification of Ancient Coins," IEEE Intelligent Systems, vol. 24, no. 2, pp. 26-34, March-April 2009, doi:10.1109/MIS.2009.29

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.