Development of a real-time focus estimaton software to be applied in two-phase flow imaging using intelligent processing

Abstract

Image processing has been an increasing research area in the last decades, especially due to crescent technological growth allied with lowering production costs. Many scientific applications have searched for establishment of quality norms associated with possible information obtainment from images. A common need from different applications has been the standardization of focus quality metric. The development of new methods for measuring the focus adjustment in order to obtain image quality metric analysis has enabled more reliable and precise data in many different industry and science sectors. Some examples are industrial equipment parts inspection using computational vision to defects classification. This work presents the initial steps to develop a methodology to estimate focus in real time in two-phase flow experiments inside tube with cylindrical geometry. This methodology is initially based on a software module using artificial intelligence methods to estimate image focus. This module is developed in LabVIEW platform using Fuzzy Logic inference base in different traditional digital focus metrics and integrated with digital cameras to increment precision on focus adjustment during two-phase flow experiments. This method will be calibrated to be used on void fraction estimation through image analysis in the natural circulation loop located at the Nuclear Engineering Center (CEN) do Instituto de Pesquisas Energéticas e Nucleares (IPEN). A set of the initial developed software modules will be presented with their respective functionalities, initial results and experimental focus estimated errors.