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Computerization of the Wartegg Test in Handwriting Analysis


Computerization of the Wartegg Test in Handwriting Analysis

Liu, Lili (2020) Computerization of the Wartegg Test in Handwriting Analysis. Masters thesis, Concordia University.

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Wartegg Test (WT) is a drawing completion task designed to reflect the personality characteristics of testers. WT is a functional and usable psychological test which is not yet well known due to the language and region barriers among worldwide researchers. It is urgent to automate WT’s psychological analysis process to let more people realize and use it, especially during the Covid-19 pandemic period, when people are asked to stay at home for a long time with limited access to in-person psychology consulting. The computerized WT allows people to attend psychology tests at home without taking the risk of virus infection. In this thesis, we proposed a system of computerizing the Wartegg test in handwriting analysis. We have implemented the image processing methods and machine learning algorithms on the Wartegg test to construct a personality analysis tool, which could mimic the evaluation process of psychologists automatically. We have extracted five features based on WT theory, they are space utilization, the numerical order of sequence, line curve ratio, animate or inanimate classification and category classification. After calculating all five features, we added them together and projected the summarized result to the Big five personality traits to get the final result. This system allows people to attend the Wartegg test at home and get the result immediately. The processing of the system has nothing to do with language and region, and only analyzes and obtains results based on drawings. Hopefully, this work could facilitate people to attend the Wartegg psychologist test with privacy security.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Liu, Lili
Institution:Concordia University
Degree Name:M. Sc.
Program:Computer Science
Date:1 December 2020
Thesis Supervisor(s):Suen, Ching Y
ID Code:987782
Deposited By: Lili Liu
Deposited On:23 Jun 2021 16:38
Last Modified:23 Jun 2021 16:38
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