Procedure for calculation of temperature profile of vacuum belt filter using thermal image recognition

Abstract

Currently thermal imaging is a big part of quality control used for multiple materials in many different fields of science. Machine vision is a rapidly developing field that can be used together with thermal imaging for automating and improving quality control process. This thesis studies viability of using thermal imaging and machine vision combined for quality control of slurry on a vacuum belt filter. Proposed machine vision system is based on use of passive thermal imaging method and OpenCV computer vision library. Results show that such system is viable for solving the goals set in this work.