Parallel texture analysis using high-order statistics and neural networks
In this paper we present a texture analysis and classification method based on the computation of high-order statistics of gray-levels or selected features. The computation of these high-order statistics can be performed in parallel in non-overlapping windows that cover the full image. Classification is performed by neural networks. In this extended summary results are presented for backpropagation networks only, but several other types of neural nets were also tested.<<ETX>>