Enhancing the Filtering-Out of the Back-to-Front Interference in Color Documents with a Neural Classifier

Back-to-front, show-through, or bleeding are the names given to the interference that appears whenever one writes or prints on both sides of translucent paper. Such interference degrades image binarization and document transcription via OCR. The technical literature presents several algorithms to remove the back-to-front noise, but no algorithm is good enough in all cases. This article presents a new technique to remove such noise in color documents which makes use of neural classifiers to evaluate the degree of intensity of the interference and besides that to indicate the existence of blur. Such classifier allows tuning the parameters of an algorithm for back-to-front interference and document enhancement.