NDLI: Classification of Ancient Epigraphs into Different Periods Using Random Forests

Content Provider	IEEE Xplore Digital Library
Author	Soumya, A. Kumar, G.H.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci. & Eng., R.V. Coll. of Eng., Bangalore, India (Soumya, A.) \|\| Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore, India (Kumar, G.H.)
Abstract	Epigraphists, who identify the ancient inscriptions, reconstruct, translate, draw conclusions about the writings, and classify their uses according to dates, are decreasing in number and also because of the fact that repetitive tasks can be exhausting for humans and prone to errors there is a need arising for the automation of these kinds of tasks. It is observed that the characters of a script have evolved over years and transformed to the current form. The purpose of this work is to estimate the period of an epigraph which is the initial step towards automating the task of reading and deciphering inscriptions. The proposed system considers a reconstructed grayscale image of an epigraph pertaining to ancient Kannada script as its input, which is binarized using Otsu's method and then segmented to characters using Connected Component analysis. Normalized Central Moments and Zernike Moments are extracted from the segmented characters and used as the feature vectors for classification. Random Forest (RF) is used as the classifier, which is an ensemble of classification trees, and each tree votes for a class and the output class is the majority of the votes which determines the era of the input epigraph. The system developed is used to classify ancient Kannada epigraphs belonging to the period of any of these dynasties: Ashoka, Satavahana, Kadamba, Chalukya, Rastrakuta and Hoysala. The system showed good results when tested on 110 Kannada epigraph images from different eras. An analysis of the prediction rate of the epigraphs was carried out and obtained a rate of 85% using RF classifier.
Starting Page	171
Ending Page	178
File Size	414294
Page Count	8
File Format	PDF
ISBN	9780769551005
DOI	10.1109/ICSIP.2014.33
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-08
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Training Image segmentation Accuracy Vegetation Normalized Central Moments and Zernike Moments Epigraphs Optical Character Recognition (OCR) Feature extraction Random Forest Classifier (RF) Classification tree analysis
Content Type	Text
Resource Type	Article

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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
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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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