Layer-based binarization for textual images

We developed a binarization approach to handle a large variety of images, from scanned flatbed images to images acquired by mobile phone cameras. The binarization is targeted at creating layers of binary images for processing by OCR engines. The layers are classified spatially and by intensity and color. First textual pixels are classified by a text operator. The text kernel is then segmented by intensity/color levels and layout analysis techniques to create regions of similar text. Finally, adaptive binarization is applied to each region to obtain superior binary images. Our experimental results show the advantages of our method over local binarization methods.