Improving the discrimination of synthetic discriminant filters
Synthetic Discriminant Filters (SDF) are theoretically capable of distortion invariant multiclass recognition. However a serious practical limitation is the trade-off between invariance and specificity. Three techniques were investigated for improving the ability of the SDF to perform 2-D rotation invariant recognition of an industrial component from amongst similarly shaped objects. The first technique involved extracting features from the correlation image. A trade-off was found between the number and/or complexity of features which must be extracted and the number of training set images in the SDF. The second technique was edge enhancing the SDF and/or test images. Edge enhancing the test images gave greater discrimination improvement than did edge enhancing the SDF. The third method was phase only filtering. Phase only SDFs gave a dramatic improvement in discrimination between training set targets and clutter although rejection of non training set targets increases. Increasing the number of training set image remedied this.
KeywordsTest Image Binary Image Correlation Image Correlation Peak Edge Image
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- Hester C.F. and Casasent D. Applied Optics, Vol 19, p 1758 (1980)Google Scholar
- Caulfield H.J. Applied Optics, Vol 21, p 4391 (1982)Google Scholar
- Oppenheim A.V. and Lim J.S. Proc. IEEE Vol 69, No 5, pp 529–541 (1981)Google Scholar
- Horner J.L. and Gianino P.D. Applied Optics, Vol 23, p 812 (1984)Google Scholar
- Horner J.L. and Gianino P.D. SPIE 519 Conference on Analogue Optical Processing and Computing pp 70–77 (1984)Google Scholar
- Cooper I.R., Nicholson M.G. and Petts C.R. IEE Proceedings, Vol 133, Part J, No. 1, pp 70–76 (1986).Google Scholar