A neural approach for thermographic image analysis

The analysis of the internal defects (not detectable by a visual inspection) of the aircraft composite materials is a difficult task unless invasive techniques are applied. In this paper we have addressed the problem of inspecting composite materials by using automatic analysis of thermographic techniques. The proposed approach consists of two steps: at first a neural network was trained to model the time space variations in a sequence of thermgraphic images and then the same neural network was applied to all the points of a sequence of thermographic images. The experimental tests were performed on a composite material and they demonstrate the ability of the method to recognize regions containing defects even in presence of considerable lighting variations.