An integrated method for classification of indus and english document images

Abstract

Unlike classification of documents with plain background and high resolution, classification of historical document, namely Indus script written on stone, wall, and palm leaves is challenging because of sources on which script is written and various handwriting, which causes noise, distortions, background variations, multisized text, and multifont. In this paper, we propose an integrated method that has two-stage algorithms to classify Indus and English from the South Indian documents. The first stage uses morphological operations and thinning on Canny of the input image to study the straightness and cursiveness of thinned components to classify the Indus document from the South Indian and English. The second stage proposes region growing and thinning to study the straightness and cursiveness of the thinned edges to classify the English from the South Indian documents. We select 100 documents for each script in total 600 documents to evaluate the performance of the method. The comparative study with existing method shows that the proposed method outperforms the existing method in terms of classification rate. © 2014 Springer India.