Devnagari document segmentation using histogram approach
Vikas J Dongre, Vijay H Mankar

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.
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Vehicle License Plate Recognition · Image Retrieval and Classification Techniques
