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Benchmark Dataset: Offline Handwritten Gurmukhi City Names for Postal Automation

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Document Analysis and Recognition (DAR 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1020))

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Abstract

Handwriting recognition delineate the computer’s ability to convert human handwriting into text that can be processed by machine. Postal automation plays a significant role in image processing and pattern recognition field. Handwritten city name recognition is the part of postal automation. For assessing the performance of the existing techniques for handwritten city name recognition, a standardized dataset proves useful. But due to lack of publicly accessible benchmark dataset in Gurmukhi script, a systematic comparison of the existing techniques for Gurmukhi city name recognition is not feasible. In this paper, we have presented a dataset for Gurmukhi postal automation named as HWR-Gurmukhi_Postal_1.0 which contains total 40,000 samples of names of various cities which are written in Gurmukhi script. This dataset can be seen as a benchmark for comparison among existing techniques for handwritten city name recognition.

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Authors and Affiliations

  1. Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, India

    Harmandeep Kaur & Munish Kumar

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  1. Harmandeep Kaur
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  2. Munish Kumar
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Correspondence to Munish Kumar .

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Editors and Affiliations

  1. Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, India

    Suresh Sundaram

  2. Computer Science and Engineering, Indian Institute of Technology Jodhpur, Karwar, Rajasthan, India

    Gaurav Harit

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Kaur, H., Kumar, M. (2019). Benchmark Dataset: Offline Handwritten Gurmukhi City Names for Postal Automation. In: Sundaram, S., Harit, G. (eds) Document Analysis and Recognition. DAR 2018. Communications in Computer and Information Science, vol 1020. Springer, Singapore. https://doi.org/10.1007/978-981-13-9361-7_14

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  • DOI: https://doi.org/10.1007/978-981-13-9361-7_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9360-0

  • Online ISBN: 978-981-13-9361-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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