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Offline Handwritten Sanskrit Character Recognition System

  1. R.Dinesh Kumar
  2. M. Kalimuthu
  3. C. Sridhathan

Abstract

Despite technological improvements, computers still lag behind in language recognition. The majority of character recognition systems are incapable of reading cracked documents or handwritten characters or words. Sanskrit, an alphabetic script, is spoken by more than 100 million people worldwide. This study is about converting scanned handwriting images into text. This contains the steps below. The scanned image is initially segmented using a spatial space detection approach, after which the images are turned into paragraphs. Then, using histogram approaches, paragraphs are segmented into lines, words, and characters. After that, it is subjected to a Support Vector Machine (SVM) extraction technique, a supervised learning algorithm for classification and these classes are mapped onto Unicode for recognition. Finally the text is reconstructed using Unicode fonts which are subjected to readable and editable documents

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