Joachim Buhmann, Martin Lades, Frank Eeckman
Changes in lighting conditions strongly effect the performance and reli(cid:173) ability of computer vision systems. We report face recognition results under drastically changing lighting conditions for a computer vision sys(cid:173) tem which concurrently uses a contrast sensitive silicon retina and a con(cid:173) ventional, gain controlled CCO camera. For both input devices the face recognition system employs an elastic matching algorithm with wavelet based features to classify unknown faces. To assess the effect of analog on -chip preprocessing by the silicon retina the CCO images have been "digitally preprocessed" with a bandpass filter to adjust the power spec(cid:173) trum. The silicon retina with its ability to adjust sensitivity increases the recognition rate up to 50 percent. These comparative experiments demonstrate that preprocessing with an analog VLSI silicon retina gen(cid:173) erates image data enriched with object-constant features.