A new adaptive edge enhancement algorithm for color laser printers

This thesis presents a novel algorithm for improving quality of edges in printed text. The algorithm is designed to add pixels at selected edge locations after halftoning. The extent of the correction is proportional to the “strength” of the edge, as determined by comparing the local differences in a four-pixel neighborhood to a dynamically generated threshold. The process is computationally efficient and requires minimal memory resources. The performance of our proposed algorithm is clearly demonstrated on several characters and lines. While the algorithm aims to improve the quality of printed text (edges), it is possible to extend its application to improvement of any edge identifiable in an image document

Adaptive Methods for Robust Document Image Understanding

A vast amount of digital document material is continuously being produced as part of major digitization efforts around the world. In this context, generic and efficient automatic solutions for document image understanding represent a stringent necessity. We propose a generic framework for document image understanding systems, usable for practically any document types available in digital form. Following the introduced workflow, we shift our attention to each of the following processing stages in turn: quality assurance, image enhancement, color reduction and binarization, skew and orientation detection, page segmentation and logical layout analysis. We review the state of the art in each area, identify current defficiencies, point out promising directions and give specific guidelines for future investigation. We address some of the identified issues by means of novel algorithmic solutions putting special focus on generality, computational efficiency and the exploitation of all available sources of information. More specifically, we introduce the following original methods: a fully automatic detection of color reference targets in digitized material, accurate foreground extraction from color historical documents, font enhancement for hot metal typesetted prints, a theoretically optimal solution for the document binarization problem from both computational complexity- and threshold selection point of view, a layout-independent skew and orientation detection, a robust and versatile page segmentation method, a semi-automatic front page detection algorithm and a complete framework for article segmentation in periodical publications. The proposed methods are experimentally evaluated on large datasets consisting of real-life heterogeneous document scans. The obtained results show that a document understanding system combining these modules is able to robustly process a wide variety of documents with good overall accuracy

A File preparation tutorial to digital printing for graphic designers

Background and Significance New technologies within the printing industry open new challenges, enable innovative ways of reaching prospective clients and bring ever more stringent demands to both graphic designers and printers. Printers must implement the emerging technologies that best suit their customers and the evolving needs of the marketplace; designers must acquaint themselves with new technologies and learn to design with respect to the output device to make best use of the equipment. A short step beyond desktop technology are digital printing systems, the culmination of many technologies that have been in various stages of development for over 20 years and have finally caught up with each other. 1 Digital printers are capable of printing directly from digital information residing in an electronic file on a computer, 2 bypassing the multiple and time-consuming steps of film output, proofing, imposition and plate-making required by traditional methods. 3 As of today, digital printing is targeted to the short-run and on-demand segments of the industry. Eventually, digital approaches will apply to just every facet of graphic communication, whether it has to a run of 1,000,000 or just one. 4 Statement of The Problem The all-time myth roaming in pressrooms that designers know nothing about printing is not entirely untrue. Often, a design is finished and approved in a studio without the minimal consideration for printing and finishing. The consolidation of a digital workflow today in the printing industry increases the need for designers to acknowledge printing in their brainstorming sessions to create designs that can be produced through emerging technologies. By doing so, they can reduce problems associated with file transfer and output such as missing images and typefaces. The ease of operation of digital presses that can receive a file and print much as a desktop printer does makes them highly attractive to designers and entrepreneurs, providing these a means for printing without all the makeready procedures associated with traditional printing processes. Statement of The Project Goals The purpose of this thesis project is to evaluate the color reproduction of digital printing systems most common in industry through the creation of a universal test instrument with respect to which all the systems will be compared. The results of the test will be used to assess the capabilities of the equipment and determine their ideal applications within the graphic communications industry. A file preparation and specification guide for each of the devices tested will be compiled. The audience at which this study is targeted is graphic designers, who could benefit by learning about the advantages and disadvantages of the various systems and learning to design with these in mind. As a result, particular attention will be paid to the impact these emerging technologies have in designers\u27 approach to producing their work. This thesis project does not suggest the equipment to be tested is the best in the market place. Its results, however, may be used in determining which system is most suitable for implementation. Methodology This thesis project will provide a color reproduction evaluation and comprehensive guides for designers to prepare and expedite files to the following digital presses: Xeikon DCP-32D Indigo E-Print 1000 Xerox DocuColor 40 Heidelberg Quickmaster-DI The criterium defining the color reproduction evaluation and the elements used in the test instrument is the following: Graphic designers, the audience at which this thesis project is targeted, think in terms of memory colors; red, green, and blue. As a result, the elements comprising the test instrument will be those which designers deal with: text and images. The printed samples will be measured with a X-Rite 938 spectrodensitometer, and the results will be complemented with a visual evaluation done under standard lighting conditions. Test Instrument The test instrument will be comprised of the following: CMYK patches and bars 4-color black patches Images of different sources and resolutions Line art Type Overprinting circles Color bars RIT Neutral Balance Target for SWOP RIT 4-Color Spokes Target Evaluation Tone reproduction Solid ink density Total ink density Gray balance Dot gain Resolution Ghosting The second part to this thesis project will involve the compilation of guides to expedite files to each output device. In addition, specifications will be collected to determine the requirements for preparing variable data printing documents

Aerospace Medicine and Biology: A continuing bibliography with indexes

This bibliography lists 319 reports, articles, and other documents introduced into the NASA scientific and technical information system in May 1986

Probabilistic framework for image understanding applications using Bayesian Networks

Machine learning algorithms have been successfully utilized in various systems/devices. They have the ability to improve the usability/quality of such systems in terms of intelligent user interface, fast performance, and more importantly, high accuracy. In this research, machine learning techniques are used in the field of image understanding, which is a common research area between image analysis and computer vision, to involve higher processing level of a target image to make sense of the scene captured in it. A general probabilistic framework for image understanding where topics associated with (i) collection of images to generate a comprehensive and valid database, (ii) generation of an unbiased ground-truth for the aforesaid database, (iii) selection of classification features and elimination of the redundant ones, and (iv) usage of such information to test a new sample set, are discussed. Two research projects have been developed as examples of the general image understanding framework; identification of region(s) of interest, and image segmentation evaluation. These techniques, in addition to others, are combined in an object-oriented rendering system for printing applications. The discussion included in this doctoral dissertation explores the means for developing such a system from an image understanding/ processing aspect. It is worth noticing that this work does not aim to develop a printing system. It is only proposed to add some essential features for current printing pipelines to achieve better visual quality while printing images/photos. Hence, we assume that image regions have been successfully extracted from the printed document. These images are used as input to the proposed object-oriented rendering algorithm where methodologies for color image segmentation, region-of-interest identification and semantic features extraction are employed. Probabilistic approaches based on Bayesian statistics have been utilized to develop the proposed image understanding techniques

Development of Impulsive Noise Detection Schemes for Selective Filtering in Images

Image Noise Suppression is a highly demanded approach in digital imaging systems design. Impulsive noise is one such noise, which is frequently encountered problem in acquistion, transmission and processing of images. In the area of image restoration, many state-of-the art filters consist of two main processes, classification (detection) and reconstruction (filtering). Classification is used to separate uncorrupted pixels from corrupted pixels. Reconstruction involves replacing the corrupted pixels by certain approximation technique. In this thesis such schemes of impulsive noise detection and filtering thereof are proposed. Impulsive noise can be Salt & Pepper Noise (SPN) or Random Valued Impulsive Noise (RVIN). Only RVIN model is considered in this thesis because of its realistic presence. In the RVIN model a corrupted pixel can take any value in the valid range. Adaptive threshold selection is emphasized for all the four proposed noise detection schemes. Incorporation of adaptive threshold into the noise detection process led to more reliable and more efficient detection of noise. Based on the noisy image characteristics and their statistics, threshold values are selected. To validate the efficacy of proposed noise filtering schemes, an application to image sharpening has been investigated under the noise conditions. It has been observed, if the noisy image passes through the sharpening scheme, the noise gets amplified and as a result the restored results are distorted. However, the prefiltering operations using the proposed schemes enhances the result to a greater extent. Extensive simulations and comparisons are done with competent schemes. It is observed, in general, that the proposed schemes are better in suppressing impulsive noise at different noise ratios than their counterparts

Pixel level data-dependent triangulation with its applications

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

On the Development of Impulsive Noise Removal Schemes

Noise Suppression from images is one of the most important concens in digital image porcessing. Impulsive noise is one such noise, which may corrupt images during their acquisitioni or transmission or storage etc.A variety of techniques are reported to remove this type of noise.It is observed that techniques which follow the two satage process of detection of noise and filtering of noisy pixels achieve better performance than others. In this thesis such schemes of impulsive noise detection and filtering thereof are proposed

The development of multi-channel inkjet printing methodologies for fine art applications

This thesis contributes to the defence of the practitioner perspective as a means of undertaking problems addressed predominantly in the field of colour science. Whilst artists have been exploring the use of colour for centuries through their personal practice and education, the rise of industrialised printing processes has generated a shift in focus away from these creative pursuits and into the computational field of colour research. It is argued here that the disposition and knowledge generated by creative practice has significant value to offer developing technologies. While creative practice has limited influence in the development of colour printing, practitioners and users of technology actively engage with the process in ways that extend beyond its intended uses in order to overcome recognised shortcomings. Here consideration is given to this creative engagement as motivation to develop bespoke printing parameters that demonstrate the effects of colour mixing through methods alternative to standard workflows. The research is undertaken incorporating both qualitative and quantitative analysis, collecting data from visual assessments and by examining spectral measurements taken from printed output. Action research is employed to directly access and act upon the constant developments in the art and science disciplines related to inkjet printing, observing and engaging with current methods and techniques employed by practitioners and developers. This method of research has strongly informed the empirical testing that has formed this thesis’s contribution to fine art inkjet printing practice. The research follows a practitioner led approach to designing and testing alternative printing methods and is aimed at expanding the number of discernible colours an inkjet printer can reproduce. The application of this methodology is evidenced through demonstrative prints and a reproduction study undertaken at the National Gallery, London. The experimentation undertaken in partnership with the National Gallery has proven the ability to increase accuracy between colour measured from the original target and reproduction, beyond the capabilities of current inkjet printing workflows