An Automatic Student Verification System Utilising Off-Line Thai Name Components

Abstract

This research proposed an automatic student identification and verification system utilising off-line Thai name components. The Thai name components consist of first and last names. Dense texture-based feature descriptors were able to yield encouraging results when applied to different handwritten text recognition scenarios. As a result, the authors employed such features in investigating their performance on Thai name component verification system. In this research, Dense-Local Binary Pattern, Dense-Local Directional Pattern, and Local Binary Pattern combined with Local Directional Pattern were employed. A base-line shape/feature i.e. Hidden Markov Model (HMM) was also utilised in this study. As there is no dataset on Thai name verification in the literature, a dataset is proposed for a Thai name verification system. The name component samples were collected from high school students. It consists of 8,400 name components (first and last names) from 100 students. Each student provided 60 genuine name components, and each of the name components was forged by 12 other students. An encouraging result was found employing the above-mentioned features on the proposed dataset.

ICFHR 2020 Competition on Short answer ASsessment and Thai student SIGnature and Name COMponents Recognition and Verification (SASIGCOM 2020)

“…For Thai name components (TNC) dataset [13], there are 6,000 (100 students × 2 name components × 30 times) genuine name components collected. For each of the genuine name components, 12 skilfully forged name components were produced.…”

“…Altogether, there are 8,400 name components in this dataset. The Thai name components [13], both genuine and forged, were obtained from 100 students, whose ages were between 12 and 16 years old.…”

“…For signature and name component verification tasks, the verifiers were trained with the first five (5) genuine samples of each writer/signer of the corresponding datasets for repeatability of the experiments and in [12,13]. The rest of the genuine samples were used for testing the false rejection rate.…”