1. A method of classifying an image comprising: generating, in a device configured to process images, features based at least in part on a block frequency domain representation of said image, wherein at least one of said features is based at least in part on one or more statistical moments generated based at least in part on at least one second order histogram of said block frequency domain representation of said image, wherein a second-order histogram is defined as h d ⁡ ( j 1 ⁢ j 2 ; ρ , θ ) = N ⁡ ( j 1 , j 2 ; ρ , θ ) N T ⁡ ( ρ , θ ) , where N(j 1 ,j 2 ;ρ,θ) is a number of pixel pairs for which the first pixel value is j 1 while the second pixel value is j 2 , where the distance between pixels is defined as ρ and the angle between pixels, with respect to horizontal, is θ, and where N T (ρ,θ) is the total number of pixel pairs in the image with separation (ρ,θ); and classifying said image based at least in part on said generated features.