Age-Type Identification and Recognition of Historical Kannada Handwritten Document Images Using HOG Feature Descriptors

  • Parashuram Bannigidad
  • Chandrashekar GudadaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 810)


Most of the historical Kannada handwritten documents are preserved in the manuscript preservation centre and archaeological departments. The historical Kannada handwritten documents are generally degraded in nature, due to this degradation, the documents are impossible to read and understand the contents. Hence, it is very much essential to restore by digitizing the historical Kannada handwritten documents and also recognize the originality of the dynasty to which it belongs. The main objective of the research work is to reconstruct, digitize and recognize the historical Kannada handwritten document images by applying image enhancement techniques and obtain the HOG feature descriptors using K-nearest neighbour (K-NN) and SVM classifiers. In this paper, we have considered historical Kannada handwritten document images of different dynasties based on their age-type; Vijayanagara dynasty (1460 AD), Mysore Wadiyar dynasty (1936 AD), Vijayanagara dynasty (1400 AD) and Hoysala dynasty (1340 AD) for experimentation. The average classification accuracy for different dynasties: in case of K-NN classifier is 92.3% and SVM classifier is 96.7%, It is observed that the SVM classifier has got a good classification performance comparatively K-NN classifier for Historical Kannada handwritten document images. The experimental outcomes are tested with manual results and other methods in the literature, which show the thoroughness of the proposed technique.


Restoration Segmentation Kannada K-NN SVM Recognition HOG Handwritten script Historical documents 



The authors are indebted to The Chairman, Department of P. G. Studies and Research in Kannada, Gulbarga University, Kalaburgi and Dept. of Hasataprati, Kannada University, Hampi for providing the historical Kannada handwritten documents and perception of manual outcomes.


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Rani Channamma UniversityBelagaviIndia

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