Forensic Analysis of Bangla Handwritten Letters

Forensic Analysis of Bangla Handwritten Letters

연구 분야: Analysis

학회: ICCCM '20: Proceedings of the 8th International Conference on Computer and Communications Management

Handwriting says a lot about a person. Sometimes the information hidden there becomes the most important clues for an investigation. Traditionally detectives take help from the Graphologists. However, given that handwriting analysis is mostly based on visual features, machine learning algorithms should be able to find out important features. In this research, we used a Bangla handwriting dataset to identify the age, gender, and location (district) of the writer using deep learning algorithms. To the best of our knowledge, we are the first to address these three features from Bangla handwriting. We found that age could be identified with around 87.2% accuracy, location with 65.2% accuracy, and gender with 55.8% accuracy. The main causes of the low accuracy are the complex geometric shapes of Bangla letters. Mastery of those shapes is clearly reflected by the age of the writers.