NDLI: Reading the legends of Roman Republican coins

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Reading the legends of Roman Republican coins

Journal on Computing and Cultural Heritage (JOCCH) : Volume 6

Journal on Computing and Cultural Heritage (JOCCH) : Volume 5

Journal on Computing and Cultural Heritage (JOCCH) : Volume 4

Journal on Computing and Cultural Heritage (JOCCH) : Volume 3

Journal on Computing and Cultural Heritage (JOCCH) : Volume 2

Journal on Computing and Cultural Heritage (JOCCH) : Volume 1

Reading the legends of Roman Republican coins

Content Provider	ACM Digital Library
Author	Kavelar, Albert Zambanini, Sebastian Kampel, Martin
Copyright Year	2014
Abstract	Coin classification is one of the main aspects of numismatics. The introduction of an automated image-based coin classification system could assist numismatists in their everyday work and allow hobby numismatists to gain additional information on their coin collection by uploading images to a respective Web site. For Roman Republican coins, the inscription is one of the most significant features, and its recognition is an essential part in the successful research of an image-based coin recognition system. This article presents a novel way for the recognition of ancient Roman Republican coin legends. Traditional optical character recognition (OCR) strategies were designed for printed or handwritten texts and rely on binarization in the course of their recognition process. Since coin legends are simply embossed onto a piece of metal, they are of the same color as the background and binarization becomes error prone and prohibits the use of standard OCR. Therefore, the proposed method is based on state-of-the-art scene text recognition methods that are rooted in object recognition. Sift descriptors are computed for a dense grid of keypoints and are tested using support vector machines trained for each letter of the respective alphabet. Each descriptor receives a score for every letter, and the use of pictorial structures allows one to detect the optimal configuration for the lexicon words within an image; the word causing the lowest costs is recognized. Character and word recognition capabilities of the proposed method are evaluated individually; character recognition is benchmarked on three and word recognition on different datasets. Depending on the Sift configuration, lexicon, and dataset used, the word recognition rates range from 29% to 67%.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	15564673
e-ISSN	15564711
DOI	10.1145/2583115
Journal	Journal on Computing and Cultural Heritage (JOCCH)
Volume Number	7
Issue Number	1
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Ancient coins OCR Coin legend recognition Local image descriptors Scene text recognition
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Conservation Computer Science Applications Information Systems

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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