, 44:141 | Cite as

Devanagari ancient documents recognition using statistical feature extraction techniques

  • Sonika Narang
  • M K Jindal
  • Munish KumarEmail author


Devanagari ancient document recognition process is drawing a lot of consideration from researchers nowadays. These ancient documents contain a wealth of knowledge. However, these documents are not available to all because of their fragile condition. A Devanagari ancient manuscript recognition system is designed for digital archiving. This system includes image binarization, character segmentation and recognition phases. It incorporates automatic recognition of scanned and segmented characters. Segmented characters may include basic characters (vowels and consonants), modifiers (matras) and various compound characters (characters formed by joining more than one basic characters). In this paper, handwritten Devanagari ancient manuscripts recognition system has been presented using statistical features extraction techniques. In feature extraction phase, intersection points, open endpoints, centroid, horizontal peak extent and vertical peak extent features are extracted. For classification, Convolutional Neural Network, Neural Network, Multilayer Perceptron, RBF-SVM and random forest techniques are considered in this work. Various feature extraction and classification techniques are considered and compared to the recognition of basic characters segmented from Devanagari ancient manuscripts. A data set, of 6152 pre-segmented samples of Devanagari ancient documents, is considered for experimental work. Authors have achieved 88.95% recognition accuracy using a combination of all features and a combination of all classifiers considered in this work by a simple majority voting scheme.


Ancient manuscripts Devanagari historical documents feature extraction classification 


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Copyright information

© Indian Academy of Sciences 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceDAV CollegeAboharIndia
  2. 2.Department of Computer Science and ApplicationsPanjab University Regional CentreMuktsarIndia
  3. 3.Department of Computational SciencesMaharaja Ranjit Singh Punjab Technical UniversityBathindaIndia

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