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Separation, Classification and Expert Mapping of Old Grantha Documents Symbols

Lalit Prakash Saxena*

* Research Scientist, Applied Research Section, Combo Consultancy, Obra UP India.

Periodicity:December - February'2019
DOI : https://doi.org/10.26634/jpr.5.4.16108

Abstract

This paper attempts to decipher old documents using symbol to script mapping scheme. Symbols are confined to documents either as isolated notations or handwritten texts with a number of not able features. This paper describes a method to separate and classify handwritten non-cursive symbols in Grantha script. This work uses statistical correlation coefficient method for separation and classification, without the recognition of the symbols. The Grantha script symbols mapping model comprises of selection, separation, preprocessing, classification, and finally mapping. The proposed model employs bounding box algorithm for locating the symbols. The algorithm selects the symbols and excludes the non-symbol components to an extent possible. For experiments, 135 Grantha script document images of varying deteriorating complexities were used. The resulting symbol classification rate (i.e., the proportion of symbols automatically classified) was obtained near to 80%, aiding in mapping to a predetermined mapping scheme.

Keywords

Grantha script, Document images, Separation, Classification, Mapping.

How to Cite this Article?

Saxena, L. P. (2019). Separation, Classification and Expert Mapping of Old Grantha Documents Symbols. i-manager’s Journal on Pattern Recognition, 5(4), 51-67. https://doi.org/10.26634/jpr.5.4.16108

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