Exploring the Opencv Library for Image Processing in Long-Pulse Thermography

Abstract

The objective of the present paper is to propose a framework, utilizing the OpenCV library, for post-processing infrared images obtained using Long-Pulse Thermography (LPT), with the goal of segmenting the images into defective and sound areas. A series of thermograms of a carbon fiber/epoxy specimen, containing precision milled flat-bottom holes, was acquired using an LPT system comprised of an uncooled microbolometer imager and halogen optical sources. Flaw detectability and planar size estimation were used to evaluate the results obtained with the proposed post-processing framework, in comparison to raw images, and images subjected only to pre-processing algorithms.