Improving object recognition by transforming Gabor filter responses
Michael Pötzsch, Norbert Krüger, Christoph von der Malsburg · Network Computation in Neural Systems · 1996
Previous work described a biologically motivated object recognition system with Gabor wavelets as basic feature type. These features are robust against slight distortion, rotation and variation in illumination. We here describe extensions of the system that address image variance due to arbitrary in-plane rotation, substantial scale changes and moderate depth rotation of objects, and to background variation, using simple linear transformation of the Gabor filter responses. The performance of the system is enhanced significantly.* This paper was presented at the Workshop on Information Theory and the Brain, held at the University of Stirling, UK, on 4–5 September 1995.