BMVC 2004, Kingston, 7th-9th Sept, 2004
Restructured Eigenfilter Matching for Novelty Detection in Random Textures
A. Monadjemi, M. Mirmehdi and B. Thomas (University of Bristol)
A new eigenfilter-based novelty detection approach to find abnormalities
in random textures is presented. The proposed algorithm reconstructs a given
texture twice using a subset of its own eigenfilter bank and a subset of a reference
(template) eigenfilter bank, and measures the reconstruction error as the
level of novelty. We then present an improved reconstruction generated by
structurally matched eigenfilters through rotation, negation, and mirroring.
We apply the method to the detection of defects in textured ceramic tiles.
The method is over 90% accurate, and is fast and amenable to implementation
on a production line.