Development of an image analysis system to produce a standardised assessment of print quality

A method has been developed using an image analysis system that simulates human print quality perception. Previous work in the area of print quality assessment has only produced methods that measure individual print quality variables, or assess small parts of an image. The image analysis system developed in this investigation is different from the previous work because it analyses the combined effects of different variables using neural network technology. In addition, measurements from an entire image can be obtained and the system can assess images irrespective of their shape. The image analysis system hardware consists of a monochrome CCD camera, a Matrox image acquisition board and a 200 MHz Pentium computer. A data pre-processing program was developed using Visual Basic version 5 to process the image data from the camera. The processed data was fed into a neural network so that empirical models of print quality could be formulated. The neural network code originated from the Matlab neural network toolbox. Backpropagation and radial basis neural network functions were used in the investigation. The hardware and software of the image analysis system were tested for non-impact printing techniques. Images of a square, a circle and text characters with dimensions of 1 cm or less were used as test images for the image analysis system. It was established that it was possible to identify the different printing processes that produced the simple shapes and text characters using the image analysis system. This was achieved by training the neural network using pre-processed image data. This produced multi-dimensional mathematical models that were used to classify the different printing processes. The classification of the different printing processes involved the objective measurement of print quality variables. Different printing processes can produce print that differs in print quality when assessed by observers. Therefore the successful classification of the printing processes demonstrated that the image analysis system could, in some cases, simulate human print quality perception. To consolidate on the preceding printing process identification result, a simulation of print quality perception was made. A neural network was trained using observer assessments of a simple pictorial image of a face. These face images were produced using a variety of different non-impact printing techniques. The neural network model was used to predict the outcomes of a further set of assessments of face images by the same observer. The accuracy of the predictions was 23 out of 24 for both the backpropagation and radial basis function neural network functions used in the test. The investigation also produced two possible practical applications for the system. Firstly, it was shown that the system has the potential to be used as a machine that can objectively assess the print quality from photocopiers. Secondly, it was demonstrated that the system might be used for forensic work, since it can identify different printing processes

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

A New framework for an electrophotographic printer model

Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations, to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the output printed images and the input images encompasses all printing distortions. The feasibility of the framework was tested with a case study modeling a monotone electrophotographic printer. The printer model was implemented as a bank of feed-forward neural networks, each one specialized in modeling a group of textural features of the printed halftone pattern. The textural features were obtained using a parametric representation of texture developed from a multiresolution decomposition proposed by other researchers. The textural properties of halftone patterns were analyzed and the key texture parameters to be modeled by the bank were identified. Guidelines for the multiresolution texture decomposition and the model operational parameters and operational limits were established. A method for the selection of training sets based on the morphological properties of the halftone patterns was also developed. The model is fast and has the capability to continue to learn with additional training. The model can be easily implemented because it only requires a calibrated scanner. The model was tested with halftone patterns representing a range of spatial characteristics found in halftoning. Results show that the model provides accurate predictions for the tone and the spatial characteristics when modeling halftone patterns individually and it provides close approximations when modeling multiple halftone patterns simultaneously. The success of the model justifies continued research of this new printer model framework

Accurate Colour Reproduction of Human Face using 3D Printing Technology

The colour of the face is one of the most significant factors in appearance and perception of an individual. With the rapid development of colour 3D printing technology and 3D imaging acquisition techniques, it is possible to achieve skin colour reproduction with the application of colour management. However, due to the complicated skin structure with uneven and non-uniform surface, it is challenging to obtain accurate skin colour appearance and reproduce it faithfully using 3D colour printers. The aim of this study was to improve the colour reproduction accuracy of the human face using 3D printing technology. A workflow of 3D colour image reproduction was developed, including 3D colour image acquisition, 3D model manipulation, colour management, colour 3D printing, postprocessing and colour reproduction evaluation. Most importantly, the colour characterisation methods for the 3D imaging system and the colour 3D printer were comprehensively investigated for achieving higher accuracy

Colour coded

This 300 word publication to be published by the Society of Dyers and Colourists (SDC) is a collection of the best papers from a 4-year European project that has considered colour from the perspective of both the arts and sciences.The notion of art and science and the crossovers between the two resulted in application and funding for cross disciplinary research to host a series of training events between 2006 and 2010 Marie Curie Conferences & Training Courses (SCF) Call Identifier: FP6-Mobility-4, Euros 532,363.80 CREATE – Colour Research for European Advanced Technology Employment. The research crossovers between the fields of art, science and technology was also a subject that was initiated through Bristol’s Festival if Ideas events in May 2009. The author coordinated and chaired an event during which the C.P Snow lecture “On Two Cultures’ (1959) was re-presented by Actor Simon Cook and then a lecture made by Raymond Tallis on the notion of the Polymath. The CREATE project has a worldwide impact for researchers, academics and scientists. Between January and October 2009, the site has received 221, 414 visits. The most popular route into the site is via the welcome page. The main groups of visitors originate in the UK (including Northern Ireland), Italy, France, Finland, Norway, Hungary, USA, Finland and Spain. A basic percentage breakdown of the traffic over ten months indicates: USA -15%; UK - 16%; Italy - 13%; France -12%; Hungary - 10%; Spain - 6%; Finland - 9%; Norway - 5%. The remaining approximate 14% of visitors are from other countries including Belgium, The Netherlands and Germany (approx 3%). A discussion group has been initiated by the author as part of the CREATE project to facilitate an ongoing dialogue between artists and scientists. http://createcolour.ning.com/group/artandscience www.create.uwe.ac.uk.Related papers to this research: A report on the CREATE Italian event: Colour in cultural heritage.C. Parraman, A. Rizzi, ‘Developing the CREATE network in Europe’, in Colour in Art, Design and Nature, Edinburgh, 24 October 2008.C. Parraman, “Mixing and describing colour”. CREATE (Training event 1), France, 2008

3D Printing of Scaffolds for Tissue Engineering

Three-dimensional (3D) printing has demonstrated its great potential in producing functional scaffolds for biomedical applications. To facilitate tissue regeneration, scaffolds need to be designed to provide a suitable environment for cell growth, which generally depends on the selection of materials and geometrical features such as internal structures and pore size distribution. The mechanical property match with the original tissue to be repaired is also critical. In this chapter, the specific request of materials and structure for tissue engineering is briefly reviewed, and then an overview of the recent research in 3D printing technologies for tissue engineering will be provided, together with a discussion of possible future directions in this area

Grayscale Digital Halftoning Using Optimization Techniques

In this paper a complete outline of advanced Digital halftoning techniques is given. This paper explains halftoning from its definition, application of halftoning to different useful techniques which are improved to give a high signal to noise ratio image. Apart from signal to noise ratio another parameter which measures the similarity between two images is also shown in this paper. Additionally the drawback of each method and comparison of the SNR, and SSIM of all methods is also shown in this paper. Error diffusion technique using FS, Stucki and JJN filters is an efficient approach to halftoning. Its main drawback is that it undergoes linear distortion. This paper is completely describing the error diffusion method and the improvements made to error diffusion so as to get a well-defined and a visually pleasing halftone image. However an evolutionary algorithms called as particle swarm optimization and Genetic Algorithm are used to create filters for the image block wise and comparing with that of the image and then finally reconstructing the whole image. In these methods of PSO and GA the cost function is formulated based on the SSIM, average minority pixel distance and the string with the best cost function value is sorted using the Evolutionary algorithms. As the human eye acts as a spatial low pass filter the image which is to be halftoned is filtered through any visual model such as a HVS model and then undergoes through the process of evolutionary algorithms

ID Photograph hashing : a global approach

This thesis addresses the question of the authenticity of identity photographs, part of the documents required in controlled access. Since sophisticated means of reproduction are publicly available, new methods / techniques should prevent tampering and unauthorized reproduction of the photograph. This thesis proposes a hashing method for the authentication of the identity photographs, robust to print-and-scan. This study focuses also on the effects of digitization at hash level. The developed algorithm performs a dimension reduction, based on independent component analysis (ICA). In the learning stage, the subspace projection is obtained by applying ICA and then reduced according to an original entropic selection strategy. In the extraction stage, the coefficients obtained after projecting the identity image on the subspace are quantified and binarized to obtain the hash value. The study reveals the effects of the scanning noise on the hash values of the identity photographs and shows that the proposed method is robust to the print-and-scan attack. The approach focusing on robust hashing of a restricted class of images (identity) differs from classical approaches that address any imageCette thèse traite de la question de l’authenticité des photographies d’identité, partie intégrante des documents nécessaires lors d’un contrôle d’accès. Alors que les moyens de reproduction sophistiqués sont accessibles au grand public, de nouvelles méthodes / techniques doivent empêcher toute falsification / reproduction non autorisée de la photographie d’identité. Cette thèse propose une méthode de hachage pour l’authentification de photographies d’identité, robuste à l’impression-lecture. Ce travail met ainsi l’accent sur les effets de la numérisation au niveau de hachage. L’algorithme mis au point procède à une réduction de dimension, basée sur l’analyse en composantes indépendantes (ICA). Dans la phase d’apprentissage, le sous-espace de projection est obtenu en appliquant l’ICA puis réduit selon une stratégie de sélection entropique originale. Dans l’étape d’extraction, les coefficients obtenus après projection de l’image d’identité sur le sous-espace sont quantifiés et binarisés pour obtenir la valeur de hachage. L’étude révèle les effets du bruit de balayage intervenant lors de la numérisation des photographies d’identité sur les valeurs de hachage et montre que la méthode proposée est robuste à l’attaque d’impression-lecture. L’approche suivie en se focalisant sur le hachage robuste d’une classe restreinte d’images (d’identité) se distingue des approches classiques qui adressent une image quelconqu