Neural network based classification using blur degradation and affine deformation invariant features

摘要

Identification of affine deformed and simultaneously blur degraded images is an important task in pattern analysis. In this paper, we introduce an image normalization approach to derive blur and affine combined moment invariants (BACIs). In our scheme, the lowest order blur invariant moments are used as the normalization constraints and an appropriate normalization procedure is designed to guarantee that the constraints used in each step should not be affected in the subsequent normalization steps. A neural network (NN) model is then employed to classify the degraded images using the proposed BACIs. Experimental results show that the system has high classification accuracy.