An Intelligent System For Writer Identification Of Devanagari Handwritten Documents Using ANN

Abstract

Many studies about writer identification have been done on different handwritten documents but less no of researches has been reported on Hindi or Devanagari documents. Here, in this technique, we accept handwriting as texture image and feature extraction done from preprocessed documents image. Significantly, the feature of presented method uses feature extraction which is suitable for structure of Hindi handwritten texts. And a new feature extraction technique is also presented which is based on classifier design. Firstly, we study different methods for feature extraction from output of preprocessing. This paper represents performance of slant estimation techniques on Devanagari handwritten documents. Slant is a unique feature; it acts as a vital role in writer identification, OCR and graphology systems. For estimation of slant, Radon Transform and Hough Transforms are applied on the word images. Further to improve the performance of these techniques, the extracted images are reconstructed using Zernike moments. For conducting this experiment, samples available on CPAR-2012 for Hindi datasets are used. The experimental result shows that slant estimated from images reconstructed using Zernike moment gives better results.

Authors and Affiliations

Praveen Sagar, Akhilesh Pandey

Keywords

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  • EP ID EP21470
  • DOI -
  • Views 283
  • Downloads 3

How To Cite

Praveen Sagar, Akhilesh Pandey (2015). An Intelligent System For Writer Identification Of Devanagari Handwritten Documents Using ANN. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(12), -. https://europub.co.uk/articles/-A-21470