Skip to main content

A Model for Determining Personality by Analyzing Off-line Handwriting

  • Conference paper
  • First Online:
Advances in Machine Learning and Data Science

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 705))

Abstract

Handwriting analysis is the scientific method or way of determining or understanding or predicting the personality or behavior of a writer. Graphology or graph analysis is the scientific name of handwriting analysis. Handwriting often called as brain writing or mind writing, since it is a system of studying the frozen graphic structures which have been generated in the brain and placed on paper in a printed or cursive style. Many things can be revealed from handwriting such as anger, morality, fears, past experience, hidden talents, mental problems. Handwriting is different from person to person. People are facing various psychological problems. Teenagers also face so many mental problems. Criminals can be detected by using handwriting analysis. Counselor and mentor can also use this tool for giving advice to clients. Proposed work contains three main steps: image preprocessing, identification of handwriting features, and mapping of identified features with personality traits. Image pre-processing is the technique in which the handwriting sample is translated into a format which can be easily and efficiently processed in further steps. These steps involve noise removal, grayscale, thresholding, and image morphology. In feature identification, there is an extraction of handwriting features. Three features of handwriting are extracted that are left margin, right margin, and word spacing. Lastly, extracted features are mapped with personality using the rule-based technique. The personality of a writer with respect to three handwriting features is displayed. The proposed system can predict 90% accurate personality of the person.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kedar, S.V., Bormane, D.S., Dhadwal, A., Alone, S., Agarwal, R.: Automatic emotion recognition through handwriting analysis: a review. In: International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, pp. 811–816, 26–27 Feb 2015

    Google Scholar 

  2. Coll, R., Fornes, A., Llados, J.: Graphological analysis of handwritten text documents for human resources recruitment. In: International Conference on Document Analysis and Recognition, pp. 1081–1085, 26–29 July 2009

    Google Scholar 

  3. Bal, A., Saha, R.: An improved method for handwritten document analysis using segmentation, baseline recognition and writing pressure detection. In: International Conference on Advances in Computing and Communications, Cochin, India, pp. 403–415, 6–8 Sept 2016

    Google Scholar 

  4. Likforman-Sulem, L., Esposito, A., Faundez-Zanuy, M., Clemencon. S.: Extracting style and emotion from handwriting. In: Advances in Neural Networks: Computational and Theoretical Issues. Smart Innovation, Systems and Technologies, vol. 37, pp. 347–355. Springer International Publishing, Switzerland (2015)

    Chapter  Google Scholar 

  5. Djamal, E.C., Darmawati, R., Ramdlan, S.N.: Application image processing to predict personality based on structure of handwriting and signature. In: International Conference on Computer, Control, Informatics and Its Applications (IC3INA), Jakarta, pp. 163–168, 19–21 Nov 2013

    Google Scholar 

  6. Champa, H.N., AnandaKumar, K.R.: Automated human behavior prediction through handwriting analysis. In: International Conference on Integrated Intelligent Computing, IEEE Computer Society Washington, DC, USA, pp. 160–165, 5–7 Aug 2010

    Google Scholar 

  7. Mutalib, S., Ramli, R., Abdul Rahman, S., Yusoff, M., Mohamed, A.: Towards emotional control recognition through handwriting using fuzzy inference. In: International Symposium on Information Technology, Kuala Lumpur, Malaysia, vol. 2, pp. 1–5, 26–28 Aug 2008

    Google Scholar 

  8. Fallah, B., Khotanlou, H.: Identify human personality parameters based on handwriting using neural network. In: Artificial Intelligence and Robotics (IRANOPEN) (IEEE), Iran, pp. 120–126, 9–9 April 2016

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vasundhara Bhade .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bhade, V., Baraskar, T. (2018). A Model for Determining Personality by Analyzing Off-line Handwriting. In: Reddy Edla, D., Lingras, P., Venkatanareshbabu K. (eds) Advances in Machine Learning and Data Science. Advances in Intelligent Systems and Computing, vol 705. Springer, Singapore. https://doi.org/10.1007/978-981-10-8569-7_35

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-8569-7_35

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8568-0

  • Online ISBN: 978-981-10-8569-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics