Automated Data Capturing And Recognition Technology To Minimize Human Intervention In University Examination System

Manual data entry from hand written data is very time consuming, tedious and prone to many errors more so where there is bulk amount of data is involved. This is the area where there is a requirement of automated data capturing and recognition technology. Using a recognition engine to convert text or handwriting from the printed page into computer readable characters saves up to 90 percent of the time it would take to enter the information manually. To fetch the data with minimal human intervention there are three types of recognition engines for this purpose and these are Optical Character Recognition (OCR), Intelligent Character Recognition (ICR) and Optical Mark Reader (OMR). Generally. OCR is best for machine print, or type, ICR is better for converting handwriting data and OMR is best suitable to detect the absence or presence of a mark, but not the shape of the mark. Automated data capturing is rapidly becoming an integral and necessary component in any organization. This not only saves the cost but also increases the speed and accuracy over manually entered data. This paper report on the study of use of these technology in various processes of examination system especially in fetching awards from OMR technology to get almost hundred percent accuracy.