Devnagari document segmentation using histogram approach

TL;DR

This paper proposes a simple histogram-based method for segmenting Devnagari documents, addressing challenges posed by the script's complex structure to improve character recognition accuracy.

Contribution

It introduces a novel histogram approach specifically designed for Devnagari script segmentation, considering its unique features and challenges.

Findings

Effective segmentation of Devnagari documents achieved

Addresses challenges in script complexity and modifiers

Improves accuracy of subsequent character recognition

Abstract

Document segmentation is one of the critical phases in machine recognition of any language. Correct segmentation of individual symbols decides the accuracy of character recognition technique. It is used to decompose image of a sequence of characters into sub images of individual symbols by segmenting lines and words. Devnagari is the most popular script in India. It is used for writing Hindi, Marathi, Sanskrit and Nepali languages. Moreover, Hindi is the third most popular language in the world. Devnagari documents consist of vowels, consonants and various modifiers. Hence proper segmentation of Devnagari word is challenging. A simple histogram based approach to segment Devnagari documents is proposed in this paper. Various challenges in segmentation of Devnagari script are also discussed.