Abstract
Optical Character Recognition finds numerous applications and one among them is in the field of Epigraphy, which is the study of inscriptions. Expert epigraphers who read ancient inscriptions are nowadays less in number. Also it is found that preserving these ancient records is important, hence lot of scope for digitization of these historical records and automatic decipherment of the same is important to the mankind. This paper addresses mainly on Segmentation, Feature Extraction and Character Recognition of Ancient Kannada script of Ashoka and Hoysala periods. Initially, input epigraph image is segmented to obtain sampled characters using Nearest Neighbor clustering Algorithm. Statistical Features such as Mean, Variance, Standard Deviation, Kurtosis, Skewness, Homogeneity, Contrast, Correlation, Energy, and Coarseness are extracted to store as training set and for comparison at the later stage of testing. Finally Mamdani Fuzzy Classifier is used in recognition; as a result, output is displayed in modern Kannada form.
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Soumya, A., Hemantha Kumar, G. (2015). Feature Extraction and Recognition of Ancient Kannada Epigraphs. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_42
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DOI: https://doi.org/10.1007/978-81-322-2202-6_42
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