Finegan, Michael K., Jr.

NASA NTRS1991

Analysis of SSME inspection imagery using AI approaches

The automated analysis of SSME injector assemblies has been investigated for the cases of LOX post surface defects and injector-baffle deterioration. Defects are isolated via 2D feature extraction from borescope and camera images; temporal-frequency transforms are then used to create a multiresolution set of feature vectors representing image contents. The potential flaws thus discriminated are then segmented and classified according to known categories. AI is applied in the form of a blackboard architecture that is controlled by a rule-based production system.

Finegan, Michael K., Jr.↗

NASA NTRS1991

Image feature extraction using Gabor-like transform

Noisy and highly textured images were operated on with a Gabor-like transform. The results were evaluated to see if useful features could be extracted using spatio-temporal operators. The use of spatio-temporal operators allows for extraction of features containing simultaneous frequency and orientation information. This method allows important features, both specific and generic, to be extracted from images. The transformation was applied to industrial inspection imagery, in particular, a NASA space shuttle main engine (SSME) system for offline health monitoring. Preliminary results are given and discussed. Edge features were extracted from one of the test images. Because of the highly textured surface (even after scan line smoothing and median filtering), the Laplacian edge operator yields many spurious edges.

Finegan, Michael K., Jr.↗