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Recognition of Handwritten Benzene Structure with Support Vector Machine and Logistic Regression a Comparative Study

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Intelligent Systems Technologies and Applications 2016 (ISTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 530))

Abstract

A chemical reaction is represented on a paper by chemical expression which can contain chemical structures, symbols and chemical bonds. If handwritten chemical structures, symbols and chemical bonds can be automatically recognized from the image of Handwritten Chemical Expression (HCE) then it is possible to automatically recognize HCE. In this paper we have proposed an approach to automatically recognize benzene structure which is the most widely used chemical compound in aromatic chemical reactions. The proposed approach can recognize benzene structure from the image of HCE. We have developed two classifiers to classify the benzene structure from HCE. The first classifier is based on Support Vector Machine (SVM) and the second classifier is based on logistic regression. The comparative study of the both classification technique is also presented in this paper. The outcome of comparison shows that both classifiers have accuracy of more than 97%. The result analysis shows that classification technique based on SVM classification performs better than classification technique using logistic regression.

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Author information

Authors and Affiliations

  1. Assistant Professor, SICSR, Symbiosis International University, Pune, MH, India

    Shrikant Mapari

  2. Professor, G H Raisoni Institute of Engineering & Technology (GHRIET), Pune, MH, India

    Ajaykumar Dani

Authors
  1. Shrikant Mapari
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  2. Ajaykumar Dani
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Corresponding author

Correspondence to Shrikant Mapari .

Editor information

Editors and Affiliations

  1. Dept. of CS, School of Science, University of Salamanca Dept. of CS, School of Science, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  2. Machine Intelligence Unit, Indian Statistical Institute Machine Intelligence Unit, Kolkata, India

    Sushmita Mitra

  3. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  4. King Fahd Univ of Petroleum and Minerals , Dhahran, Saudi Arabia

    El-Sayed El-Alfy

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Mapari, S., Dani, A. (2016). Recognition of Handwritten Benzene Structure with Support Vector Machine and Logistic Regression a Comparative Study. In: Corchado Rodriguez, J., Mitra, S., Thampi, S., El-Alfy, ES. (eds) Intelligent Systems Technologies and Applications 2016. ISTA 2016. Advances in Intelligent Systems and Computing, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-319-47952-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-47952-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47951-4

  • Online ISBN: 978-3-319-47952-1

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