Fuzzy edge-symmetry features for improved intruder detection

The paper proposes a new set of fuzzy features based on symmetry of edges for improving the accuracy of detecting intruders. We show that the proposed fuzzy edge-symmetry feature-based classifier is comparable to the detection accuracy of a multi-scale wavelet feature system for intruder detection. We also present two approaches to fusing the results of classifiers trained independently on the edge-symmetry and wavelet features. Experimental results clearly indicate the improvement in system performance when the results of the two classifiers are fused.