Towards an Universal Approach to Background Removal in Images of Bankchecks

This paper is concerned with an approach to the automated design of lters for background removal of bankchecks. The approach is derived from a simpli ed version of the morphological subtraction and its interpretation, using the 2DHistogram. From an empty bankcheck, a mask is computed, which can be added to every lled-in bankcheck of the same kind, ltering the user entered information parts within the bankcheck image. This approach works well for many types of bankchecks, but it fails for EC bankchecks. By considering the 2DHistogram of empty and lled-in EC bankcheck images, a means is given for improving the result for EC checks, using the so-called 2D-Lookup algorithm. Moreover, this algorithm allows for the use of the lled-in image only, if there is a way to specify two lter operations, which process the lled-in image in order to get a separable 2D-Histogram. An evolutionary algorithm, the genetic programming (GP), is used for performing this adaptation task. The evolutionary generated lters shows very good performance for EC bankcheck background removal. A detailed study gives the importance of a family of image processing operations, the OWA operations, for this removal.