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CNN based recognition of handwritten multilingual city names

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Abstract

It is important to recognize the destination city name correctly for a postal document to reach its desired address. In India people often mix up scripts while writing the address. Often the script of the destination city name is different from the other part of the postal document. This is common in India due to the multilingual and multi script nature of the country. In this paper, a Convolutional Neural Network (CNN) based approach towards the recognition of handwritten multilingual multiscript Indian city names is presented. Experiments were performed not only in a single script scenario but also in multi script, considering English, Bangla and Devanagari scripts. An accuracy of 91.72% was obtained on 106 city names in mixed script scenario from the proposed scheme and the data set will be made available to the researcher on request. Further experiments were also performed with different script combinations and obtained results up to 98.01%. The system also produced a mean performance difference of approximately ± 1% for successive changes in the data set size, thereby pointing to the robustness of the proposed architecture.

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Authors and Affiliations

  1. St. Xavier’s College (Autonomous), Kolkata, India

    Ramit Kumar Roy

  2. Department of Computer Science, West Bengal State University, Kolkata, India

    Himadri Mukherjee & Kaushik Roy

  3. CVPR Unit, Indian Statistical Institute, Kolkata, India

    Umapada Pal

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  1. Ramit Kumar Roy
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  2. Himadri Mukherjee
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  3. Kaushik Roy
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  4. Umapada Pal
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Correspondence to Kaushik Roy.

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Roy, R.K., Mukherjee, H., Roy, K. et al. CNN based recognition of handwritten multilingual city names. Multimed Tools Appl 81, 11501–11517 (2022). https://doi.org/10.1007/s11042-022-12193-8

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  • DOI: https://doi.org/10.1007/s11042-022-12193-8

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