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A novel skew correction methodology for handwritten words in multilingual multi-oriented documents

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Abstract

Multi-oriented handwritten documents require additional preprocessing for segmentation and subsequent phases to work accurately in handwritten recognition systems. Skew correction is one such additional phase. Appearance of skew in multi-oriented Indian language based handwritten document is higher due to the presence of cursive nature. In the current work, we utilise a salient feature present in Indian scripts called \(m\bar {a}\)tr\(\bar {a}\) (also known as headline), extract a group of eligible pixels, and employ linear curve fitting for detecting and correcting skew in handwritten words. The proposed method is capable of correcting skew in four distinct Indian languages, viz. Bangla, Hindi, Marathi, and Punjabi. It is capable of efficiently handling skewed word images to an extent of ± 55∘ and delivers precise result even when the \(m\bar {a}\)tr\(\bar {a}\) is mostly absent or discontinuous.

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Authors and Affiliations

  1. Department of Computer Science, BITS Pilani, Dubai Campus, PO Box 345055, Dubai, UAE

    Rahul Pramanik

  2. Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad -, Dhanbad, 826004, India

    Soumen Bag

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  1. Rahul Pramanik
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  2. Soumen Bag
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Correspondence to Rahul Pramanik.

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Rahul Pramanik declares that he has no conflict of interest. Soumen Bag declares that he has no conflict of interest.

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Pramanik, R., Bag, S. A novel skew correction methodology for handwritten words in multilingual multi-oriented documents. Multimed Tools Appl 80, 27323–27342 (2021). https://doi.org/10.1007/s11042-021-10822-2

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