Image binarization, the conversion of a color image into its monochromatic version, plays a key role in many document processing pipelines. The technical literature presents over a hundred different algorithms for document image binarization yielding different quality results, depending on the intrinsic features of the document image. In addition, their processing times vary significantly, influencing their applicability. The fundamental question here is: Which binarization scheme should one choose, from all the available ones, to provide a reasonable quality-time monochromatic image? A recently published paper shows that the analysis of the texture of the paper background of a scanned document may offer elements to select an appropriate binarization algorithm. This work extends such results by analyzing twelve texture descriptors using three distinct distance measures to evaluate 315 binarization schemes, providing solid evidence that the analysis of the paper texture may guide the selection of a suitable binarization algorithm for a given scanned document image.

Many document processing platforms have image binarization as a key step. The performance of binarization algorithms depends on several factors that span from the quality of the digitalization devices to the intrinsic features of the document itself and the kind and intensity of the noises present in the image. Besides that, the processing time is also an important factor that may restrict the applicability of a given algorithm. This competition on binarizing photographed documents assessed the quality, time, space, and performance of twenty three new algorithms and seventy-five "classical" algorithms. The test dataset is composed of offset and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on, off, and in auto modes under two different angles and places of capture.

Document image binarization is a fundamental step in many document processes. No binarization algorithm performs well on all types of document images, as the different kinds of digitalization devices and the physical noises present in the document and acquired in the digitalization process alter their performance. Besides that, the processing time is also an important factor that may restrict its applicability. This competition on binarizing photographed documents assessed the quality, time, space, and performance of five new algorithms and sixty-four "classical" and alternative algorithms. The evaluation dataset is composed of laser and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on and off, under two different angles and places of capture.

Today, over eighty percent of the world's population owns a smart-phone with an in-built camera, and they are very often used to photograph documents. Document binarization is a key process in many document processing platforms. This competition on binarizing photographed documents assessed the quality, time, space, and performance of five new algorithms and sixty-four "classical" and alternative algorithms. The evaluation dataset is composed of offset, laser, and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on and off, under two different angles and places of capture.

Most of the best known binarization algorithms have grayscale conversion as a pre-processing step, before applying the binarization strategy itself. Many algorithms produce equally good or even better quality images if fed with only one component of the image, instead of its gray-scale/luminance equivalent. The time-gain here is obtained in avoiding the several floating-point calculations in converting a RGB-color image into grayscale. More than 60 binarization algorithms were tested using "real-world" images.

Detecting the age of a document is an important subject for forensic purposes. As the paper ages, its color changes depending on a number of factors such as its original color, storage conditions, environment temperature, humidity, etc. In Brazil, documents such and birth and wedding certificates during the second half of the 20th century used standardized preprinted forms. This paper proposes a model for determining the age of such documents based on the color components of the background of its scanned image.

Very often interested readers highlight documents with felt pens. Such marking may be seen as personal view of the most important aspects of the document, which are used to instantly draw the readers' attention at. This article addresses ways of using the highlighting made by the reader of a book or a paper documents to automatically generate its text summary.