Techniques for document image processing in compressed domain

The main objective for image compression is usually considered the minimization of storage space. However, as the need to frequently access images increases, it is becoming more important for people to process the compressed representation directly. In this work, the techniques that can be applied directly and efficiently to digital information encoded by a given compression algorithm are investigated. Lossless compression schemes and information processing algorithms for binary document images and text data are two closely related areas bridged together by the fast processing of coded data. The compressed domains, which have been addressed in this work, i.e., the ITU fax standards and JBIG standard, are two major schemes used for document compression. Based on ITU Group IV, a modified coding scheme, MG4, which explores the 2-dimensional correlation between scan lines, is developed. From the viewpoints of compression efficiency and processing flexibility of image operations, the MG4 coding principle and its feature-preserving behavior in the compressed domain are investigated and examined. Two popular coding schemes in the area of bi-level image compression, run-length and Group IV, are studied and compared with MG4 in the three aspects of compression complexity, compression ratio, and feasibility of compressed-domain algorithms. In particular, for the operations of connected component extraction, skew detection, and rotation, MG4 shows a significant speed advantage over conventional algorithms. Some useful techniques for processing the JBIG encoded images directly in the compressed domain, or concurrently while they are being decoded, are proposed and generalized; In the second part of this work, the possibility of facilitating image processing in the wavelet transform domain is investigated. The textured images can be distinguished from each other by examining their wavelet transforms. The basic idea is that highly textured regions can be segmented using feature vectors extracted from high frequency bands based on the observation that textured images have large energies in both high and middle frequencies while images in which the grey level varies smoothly are heavily dominated by the low-frequency channels in the wavelet transform domain. As a result, a new method is developed and implemented to detect textures and abnormalities existing in document images by using polynomial wavelets. Segmentation experiments indicate that this approach is superior to other traditional methods in terms of memory space and processing time

A survey of computer uses in music

This thesis covers research into the mathematical basis inherent in music including review of projects related to optical character recognition (OCR) of musical symbols. Research was done about fractals creating new pieces by assigning pitches to numbers. Existing musical pieces can be taken apart and reassembled creating new ideas for composers. Musical notation understanding is covered and its requirement for the recognition of a music sheet by the computer for editing and reproduction purposes is explained. The first phase of a musical OCR was created in this thesis with the recognition of staff lines on a good quality image. Modifications will need to be made to take care of noise and tilted images that may result from scanning

The contour tree image encoding technique and file format

The process of contourization is presented which converts a raster image into a discrete set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimises noticeable artifacts in the simplified image. The contour merging technique offers a complementary lossy compression system to the QDCT (Quantised Discrete Cosine Transform). The artifacts introduced by the two methods are very different; QDCT produces a general blurring and adds extra highlights in the form of overshoots, whereas contour merging sharpens edges, reduces highlights and introduces a degree of false contouring. A format based on the contourization technique which caters for most image types is defined, called the contour tree image format. Image operations directly on this compressed format have been studied which for certain manipulations can offer significant operational speed increases over using a standard raster image format. A couple of examples of operations specific to the contour tree format are presented showing some of the features of the new format.Science and Engineering Research Counci

Non-Visual Representation of Complex Documents for Use in Digital Talking Books

Essential written information such as text books, bills, and catalogues needs to be accessible by everyone. However, access is not always available to vision-impaired people. As they require electronic documents to be available in specific formats. In order to address the accessibility issues of electronic documents, this research aims to design an affordable, portable, standalone and simple to use complete reading system that will convert and describe complex components in electronic documents to print disabled users

Image Processing Using FPGAs

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs

Digital imaging technology assessment: Digital document storage project

An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes

Chart recognition and interpretation in document images

Ph.DDOCTOR OF PHILOSOPH

2D-barcode for mobile devices

2D-barcodes were designed to carry significantly more data than its 1D counterpart. These codes are often used in industrial information tagging applications where high data capacity, mobility, and data robustness are required. Wireless mobile devices such as camera phones and Portable Digital Assistants (PDAs) have evolved from just a mobile voice communication device to what is now a mobile multimedia computing platform. Recent integration of these two mobile technologies has sparked some interesting applications where 2D-barcodes work as visual tags and/or information source and camera phones performs image processing tasks on the device itself. One of such applications is hyperlink establishment. The 2D symbol captured by a camera phone is decoded by the software installed in the phone. Then the web site indicated by the data encoded in a symbol is automatically accessed and shown in the display of the camera phone. Nonetheless, this new mobile applications area is still at its infancy. Each proposed mobile 2D-barcode application has its own choice of code, but no standard exists nor is there any study done on what are the criteria for setting a standard 2D-barcode for mobile phones. This study intends to address this void. The first phase of the study is qualitative examination. In order to select a best standard 2D-barcode, firstly, features desirable for a standard 2D-barcode that is optimized for the mobile phone platform are identified. The second step is to establish the criteria based on the features identified. These features are based on the operating limitations and attributes of camera phones in general use today. All published and accessible 2D-barcodes are thoroughly examined in terms of criteria set for the selection of a best 2D-barcode for camera phone applications. In the second phase, the 2D-barcodes that have higher potential to be chosen as a standard code are experimentally examined against the three criteria: light condition, distance, whether or not a 2D-barcode supports VGA resolution. Each sample 2D-barcode is captured by a camera phone with VGA resolution and the outcome is tested using an image analysis tool written in the scientific language called MATLAB. The outcome of this study is the selection of the most suitable 2D-barcode for applications where mobile devices such as camera phones are utilized

Parametric classification in domains of characters, numerals, punctuation, typefaces and image qualities

This thesis contributes to the Optical Font Recognition problem (OFR), by developing a classifier system to differentiate ten typefaces using a single English character ‘e’. First, features which need to be used in the classifier system are carefully selected after a thorough typographical study of global font features and previous related experiments. These features have been modeled by multivariate normal laws in order to use parameter estimation in learning. Then, the classifier system is built up on six independent schemes, each performing typeface classification using a different method. The results have shown a remarkable performance in the field of font recognition. Finally, the classifiers have been implemented on Lowercase characters, Uppercase characters, Digits, Punctuation and also on Degraded Images

Remote Sensing Data Compression

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interestin