Off-Line Handwritten Bilingual Name Recognition for Student Identification in an Automated Assessment System

Abstract

The Student name Identification System (SIS) proposed here was investigated for English and Thai languages combined. The proposed system recognises each name by using an approach for whole word recognition. In the proposed system, the Gaussian Grid Feature (GGF), and Modified Direction Feature (MDF), together with a proposed hybrid feature extraction technique called Water Reservoir, Loop and Gaussian Grid Feature (WRLGGF) were investigated on full word contour images of each name sample; Artificial neural networks and support vector machines were used as classifiers. An encouraging recognition accuracy of 99.25% was achieved employing the proposed technique compared to 98.59% for GGF, and 96.63% using MDF.

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

“…Hence it can be concluded that an appreciating verification accuracy is attended in the experiment, although there is a huge scope of development in the forgery experiments. : Comparison of verification rates attained between the proposed study and the techniques [4], [5], [6], and [12] found in the literature given the similar datasets nature.…”

“…The verification rates decreased fractionally, and therefore, the results were not included in the table. The closest work which can be used for comparison were the work proposed by [4], [5], [6], and [12]. The first three studies' results were obtained from SIS which used name components for identification process.…”

“…The first three studies' results were obtained from SIS which used name components for identification process. Whereas [4] and [6] were using only Thai name components, the work in [5] was employing bilingual name components being English and Thai languages. In such work, only identification process was taken place.…”

“…Feature extraction techniques used in the studies were Modified Direction Features (MDF), Gaussian Grid Feature (GGF), and Water Reservoir, Loop and Gaussian Grid Feature (WRLGGF). Because in this research, the authors were focus on verification system, the feature extraction techniques besides the ones employed [4], [5], and [6] were not utilised in this occasion, it was, however, planned to be used in the future work.…”

“…This research proposed an automatic Student Verification System (SVS) using student name components. This research was an extension from Student Identification Systems (SIS) which were proposed in [4], [5]; the SISs were developed to identify students, so that their marks which were produced from handwritten short answer assessment system [6] can be recorded accordingly. In [4], [5], and [6], student name components were used to identify students, the student numbers were not used as it was planned that the verification system using the name components could be developed.…”