Detection of Personality Using Machine Learning

Authors

  • Anshal Aggarwal
  • Penmetsa Shrujan Varma
  • Lakshitaa Sehgal
  • Kunjal Prashant Shah
  • Gunda Umamaheshwar Gupta
  • Siddhartha Ranjan

Keywords:

forensic handwriting exam, graphology, handwriting, Machine Learning, OCR

Abstract

Data that include the dynamically captured route, stroke, distance, length, strain and form of an individual's signature allow handwriting to be a dependable indicator of a character's identification. Forensic handwriting exam has a new frontier: the virtual signature in the biometric modality that uses, for popularity functions, the anatomic and behavioral traits that a person showcases when signing her/his name. Handwriting examiners regularly must determine if the signature is proper or simulated, dynamic information along with velocity and stress are fundamental and may be expected qualitatively. A person's handwriting is as particular as their personal, which makes it tempting to attach the two. Graphology is the analysis of the physical characteristics and styles of handwriting which will identify the author, indicating the mental country at the time of writing, or evaluating character traits. It is typically considered a pseudoscience.

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Published

07-01-2022

How to Cite

[1]
A. Aggarwal, P. S. Varma, L. Sehgal, K. P. Shah, G. U. Gupta, and S. Ranjan, “Detection of Personality Using Machine Learning”, IJRESM, vol. 5, no. 1, pp. 46–50, Jan. 2022.

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