Visual Data Acquisition for Measuring Devices using Deep Learning

Abstract

Most of the measurement devices in the university labs are not computerized. Hence, unsteady measurements are difficult to capture. In order to retrieve the measured data to computers, expensive data acquisition systems are needed to link these devices to computers. To overcome this issue a cost-efficient solution is proposed. This article proposes a methodology to convert the readings of LCDs of the various measuring devices into a digital form using computer vision. The procedure is successfully implemented and the results are presented.