| dc.contributor.author | Hewa Meegasthenna Gamage, Avishka | |
| dc.date.accessioned | 2022-12-20T10:52:43Z | |
| dc.date.available | 2022-12-20T10:52:43Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | Hewa Meegasthenna Gamage, Avishka (2022) GrafoEye - Big Five personality prediction using handwriting analysis. BEng. Dissertation, Informatics Institute of Technology | en_US |
| dc.identifier.issn | 2018407 | |
| dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/1220 | |
| dc.description.abstract | "Personality identification through handwriting analysis (Graphology) plays a vital role in various fields like employee recruitment, counselling, personality development etc. With the expansion of usages in Graphology, there were problems like less availability of graphologists, high hiring cost and time consuming. Therefore this research is focused on providing mobile application solution for predicting the most possible Big-Five personality group among the 5 groups which are included in Big-Five personality taxonomy by analyzing handwriting sample using various image-processing techniques and extracts 11 handwriting features. An Ensemble learning approach is used for creating the model. Trained model for multi-class classification predicts the most possible Big-Five personality group according to the correlation between handwriting features and Big-Five personality groups in published research papers." | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Image processing | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Ensemble learning | en_US |
| dc.subject | Graphology | en_US |
| dc.title | GrafoEye - Big Five personality prediction using handwriting analysis | en_US |
| dc.type | Thesis | en_US |