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A comparative study of graphic symbol recognition methods

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Abstract

From the very beginning of written scripts, contents of documents generally comprise of text, images, figures, graphs and graphic symbols. A graphic recognition system involves representation of graphic symbols, description of features extracted from the symbol and classification of the unknown symbols. Due to the wide range of symbols, no generalize technique is available that can recognize the symbol for all the application domains. this paper, we present an overview of the many models and methodologies available to symbol recognition for representation, description and classification. We provide a general survey of symbol recognition process, beginning with the basic definition of symbol, which is further classified into their types based on application areas. distinctive part of the survey is categorization of different symbol recognition methods into four categories i.e. statistical, structural, syntactical and hybrid methods, which is aimed to help potential researchers in exploring areas of research in the field of graphic symbol recognition.

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Authors and Affiliations

  1. Sarhad University of Science and Information Technology, Peshawar, Pakistan

    Irshad Khan & Murad Khan

  2. Islamia College University, Peshawar, Pakistan

    Naveed Islam

  3. FAST-National University of Computer and Emerging Sciences, Peshawar, Pakistan

    Hafeez Ur Rehman

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  1. Irshad Khan
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  2. Naveed Islam
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  3. Hafeez Ur Rehman
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  4. Murad Khan
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Khan, I., Islam, N., Ur Rehman, H. et al. A comparative study of graphic symbol recognition methods. Multimed Tools Appl 79, 8695–8725 (2020). https://doi.org/10.1007/s11042-018-6289-6

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