-In spite of several advancements in technologies pertaining to Optical character recognition, handwriting continues to persist as means of documenting information for day-to-day life. The process of segmentation and recognition pose quiets a lot of challenges especially in recognizing cursive hand-written scripts of different languages. The concept proposed is a solution crafted to perform character recognition of hand-written scripts in Tamil, a language having official status in India, Sri Lanka, and Singapore. The approach utilizes discrete Hidden Markov Models (HMMs) for recognizing off-line cursive handwritten Tamil characters. The tolerance of the system is evident as it can overwhelm the complexities arise out of font variations and proves to be flexible and robust. Higher degree of accuracy in results has been obtained with the implementation of this approach on a comprehensive database and the precision of the results demonstrates its application on commercial usage. The methodology promises to present a simple and fast scaffold to construct a full OCR system extended with suitable pre-processing.
In the last three decades, the field of e-assessment has become more important. Several universities and higher education institutes have started to provide online assessments. The variance in the e-assessment application domains as well as the market competition has caused several e-assessment systems to be developed. As the universities cover different subjects and courses, they may have more than one e-assessment system based on the department and the course. Therefore, more resources and budgeting planes are required. This paper discusses the possibility of a generic and flexible e-assessment system as a way to solve this problem. Furthermore, it investigates the generality and flexibility requirements in the field of e-assessment and provides appropriate architecture for a modular assessment system with reference to these requirements.
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