Multimed Tools Appl https://doi.org/10.1007/s11042-018-6289-6 A comparative study of graphic symbol recognition methods Irshad Khan 1 · Naveed Islam 2 · Hafeez Ur Rehman 3 · Murad Khan 1 Received: 28 February 2018 / Revised: 27 May 2018 / Accepted: 18 June 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract From the very beginning of written scripts, contents of documents generally comprise of text, images, figures, graphs and graphic symbols. A graphic recognition sys- tem 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 avail- able to symbol recognition for representation, description and classification. We provide a general survey of symbol recognition process, beginning with the basic definition of sym- bol, 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. Keywords Symbol recognition · Object recognition and classification  Irshad Khan irshad.csit@suit.edu.pk Naveed Islam naveed.islam@icp.edu.pk Hafeez Ur Rehman hafeez.urrehman@nu.edu.pk Murad Khan murad.csit@suit.edu.pk 1 Sarhad University of Science and Information Technology, Peshawar, Pakistan 2 Islamia College University, Peshawar, Pakistan 3 FAST-National University of Computer and Emerging Sciences, Peshawar, Pakistan