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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Character Segmentation from Offline Handwritten Gujarati Script Documents
verfasst von : Mit Savani, Dhrumil Vadera, Krishn Limbachiya, Ankit Sharma
Erschienen in: Information and Communication Technology for Competitive Strategies (ICTCS 2021)
Verlag: Springer Nature Singapore
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Abstract
Modern innovations make great impacts on the human lifestyle and their way of working. It boosts the efficiency and productivity of people by reducing efforts, which help to handle several tasks at a time. Nowadays, all the government offices, banks, businesses, and education systems are influenced by paperless technology. It improves documentation and the secure sharing of information by saving space and resources. Paperless technology works on Optical Character Recognition (OCR) to convert all physical documents into machine-based documents. OCR consists of mainly two steps: segmentation, and recognition. The success rate of character recognition depends on the segmentation of required regions of interest. This paper introduced an algorithm that utilized projection profile, bounding box, and connected component labeling techniques for the development of Gujarati handwritten dataset and segmentation of handwritten text from Gujarati documents into line, word, and characters.