Optimum binarization of technical document images

We present a high quality solution to the binarization problem of technical document images. The method is based on locally adaptive methods without the need of manual interaction or tuning. The algorithm includes Niblack´s (1986) binarization and two validation steps based on morphological image processing and gradient based decisions. Our result has the following advantages. Alphanumeric labels are restored, even if they are hardly readable in the source image. Parallel, multiple lines with small distance are reconstructed. Even detail of very low contrast in the vicinity of strong contrast image areas is reconstructed (e.g. faint stamp lines). Variable background intensity is suppressed, but texture and large font bold face letters are restored