The increasing availability of high performance, low priced, portable digital imaging devices has created a tremendous opportunity for supplementing traditional scanning for document image acquisition. Digital cameras attached to cellular phones, PDAs, or as standalone still or video devices are highly mobile and easy to use; they can capture images of any kind of document including very thick ...

A particularly effective method for analyzing document images, that consist of large numbers of binary pixels, is to generate reduced images whose pixels represent enhancements of textural densities in the full-resolution image. These reduced images are generated using an integrated combination of filtering and subsampling. Previously reported methods used thresholding over a square grid, and c...

The rapid growth of digital libraries (DLs) worldwide poses many new challenges for document image analysis (DIA) research and development. DLs promise to offer more people access to larger document collections, and at far greater speed, than physical libraries can. But DLs also tend, for many reasons, to serve poorly, or even to omit entirely, many types of non-digital human–legible media, suc...

Even if font usage plays an important role in Document Image Analysis (DIA), recognition systems generally take the concept of font management in a weaker sense than in the production cycle. With the point of view of the document recognition community, we show how typographic information (characters bitmap, metrics, etc.) can improve existing analysis methods. After a brief survey of font recog...

This paper describes the Document Image Understanding Toolbox currently under development at the University of Washington’s Intelligent Systems Laboratory The Toolbox provides a common data structure and a variety of document image analysis and understanding algorithms from which Toolbox users can construct document image processing systems. An algon’thms for font attribute recognition based on...

Document image enhancement methods are often used to improve the accuracy and efficiency of automated document analysis recognition tasks such as character recognition. These images could be degraded or damaged for various reasons including aging, fading handwriting, poor lighting conditions, watermarks, etc. In recent years, with improvement computer performance continuous development deep lea...

Document Image Binarization converts a gray-scale document image into binary document image .It is usually performed in the pre-processing stage of document image analysis and it aims to segment the foreground text from the document background. Segmentation of foreground text from the document background is a difficult task in the case of degraded document images. In this paper we propose a sim...

The digitization of documents and their availability over the network demands solution toward content based document image analysis, indexing, searching and retrieval. Signature, Logo and Layout of the documents present convincing evidence and provide an important form of indexing for effective document image retrieval in a variety of applications. This paper describes methods and techniques de...