Human Personality Prediction Using Automated Handwriting Analysis

Project Title

Project Area of Specialization

Artificial Intelligence

Project Summary

We propose a methodology based on artificial intelligence models that aim to determine the Big Five personality traits of an individual by analyzing handwriting. These five personality traits are Extraversion, Agreeableness, Openness, Conscientiousness, and Neuroticism. Our personalities affect the way our handwriting develops because handwriting is the pattern of our psychology expressed in symbols on the page and these symbols are as unique as our DNA.

Project Objectives

To Predict human personality using automated handwriting analysis.
To increase the accuracy of predicted result.
To provide fast response time to grasp user's attention.
Result will be Precise and authentic.
Provide a facility to maintain person’s record in database.

Project Implementation Method

Our project is a combination of two sciences i.e.
Psychology (the science of mind and behavior), and computer science.
Our project implementation is also based on two main models. The first model is the Rule-based model in which we have defined personality traits parallel to certain handwriting features such as slants, zones, and baselines etc.
The second model is the Graphological model in which automated handwriting analysis will be performed. Handwriting analysis consists of few steps. Firstly, some image processing techniques are applied to the handwritten sample provided by the user to extract handwriting. The next step is to perform segmentation on every row, each word, and individual letters. After extracting features through segmentation, the classification is performed using artificial intelligence models. In order to improve accuracy, the repetitiveness of traits is considered and the dominant trait is fetched.

Benefits of the Project

Our application will provide a base for automating graphology and in future after further research and work, it can create a remarkable change.
Manual process of handwriting analysis is costly, lengthy and prone to fatigue, our proposed system can be used as a twin tool by graphologist to improve the accuracy and anticipate the emotions of a person faster.
Our application will be useful for doctors; they will be able to keep track of mental state of their patients.
All those people who are unable to speak properly, this application will help their families in order to understand their emotions.
As our application will be user friendly and free of cost so anyone will be able to use it.

Technical Details of Final Deliverable

The final deliverable will be a user-friendly desktop application. The application interface will enable the user to login by providing necessary details. After signing up, user will be able to upload a handwritten sample image in any desireable format such png,jpg etc. In backend processing, firstly, our model will apply image processing techniques such as removing noise, contour smoothening and converting the image into BGR representation. After applying image processing techniques, the next step is to perform segmentation to extract features. After extracting features, the classification is performed on these features using artificial intelligence models such as Convolutional Neural Network.
The Final report will be generated based on prominent traits fetched from automated handwriting analysis. Report will be precised and authentic. User information will be stored in database for detail personality analysis.