1. A method for analyzing an input image x with K 1 ×K 2 pixels x (r,s) where (r,s) denotes the pixel location with r=1, 2,. .. , K 1 indicating the image row, and s=1, 2,. .. , K 2 indicating the image column, the input image being one of a digitized image stored in a memory or a scanned image from a scanner, comprising: using a processor to form a feature image z from the input image x by: dividing the input image x into a plurality of blocks of pixels each block having a block size of g 1 ×g 2 pixels, where g 1 denotes a number of image rows in a block and g 2 denotes a number of image columns in a block, associating each block of pixels in the input image x with a single pixel in the feature image z, with the feature image z consisting of K 1 /g 1 ×K 2 /g 2 pixels, and outputting the feature image z for further analysis or storage in a memory, wherein the feature image z is a two-channel image with feature pixels z (m,n) =[f (m,n) ,b (m,n) ], for m=1, 2,. .. , K 1 /g 1 and n=1, 2,. .. , K 2 /g 2 , wherein f (m,n) and b (m,n) denote, respectively, the foreground and background components of a feature pixel z (m,n) , wherein the foreground and background components of a feature pixel z (m,n) are respectively defined as follows: 
 f (m,n) =min{ x (r,s) ;( m− 1) g 1 <r≦mg 1 ,( n− 1) g 2 <s≦ng 2 } 
 b (m,n) =max{ x (r,s) ;( m− 1) g 1 <r≦mg 1 ,( n− 1) g 2 <s≦ng 2 } where min and max are the minimum and maximum operators, and wherein the processor detects pages according to: d ( m , n ) = { 1 for b ( m , n ) - f ( m , n ) < θ and b ( m , n ) > ϑ 0 otherwise. where θ and φ are tunable parameters used to evaluate a similarity between a foreground and a background in input image x and identify pixels with high contributions of background and foreground components, and wherein d (m,n) is a pixel in a binary map d of dimensions identical to that of the feature image z, and the value d (m,n) =1 indicates that the location (m,n) in the feature image z corresponds to a page area.