Estimating toner usage with laser electrophotographic printers, and object map generation from raster input image

Accurate estimation of toner usage is an area of on-going importance for laser, electrophotographic (EP) printers. In Part 1, we propose a new two-stage approach in which we first predict on a pixel-by-pixel basis, the absorptance from printed and scanned pages. We then form a weighted sum of these pixel values to predict overall toner usage on the printed page. The weights are chosen by least-squares regression to toner usage measured with a set of printed test pages. Our two-stage predictor significantly outperforms existing methods that are based on a simple pixel counting strategy in terms of both accuracy and robustness of the predictions.^ In Part 2, we describe a raster-input-based object map generation algorithm (OMGA) for laser, electrophotographic (EP) printers. The object map is utilized in the object-oriented halftoning approach, where different halftone screens and color maps are applied to different types of objects on the page in order to improve the overall printing quality. The OMGA generates object map from the raster input directly. It solves problems such as the object map obtained from the page description language (PDL) is incorrect, and an initial object map is unavailable from the processing pipeline. A new imaging pipeline for the laser EP printer incorporating both the OMGA and the object-oriented halftoning approach is proposed. The OMGA is a segmentation-based classification approach. It first detects objects according to the edge information, and then classifies the objects by analyzing the feature values extracted from the contour and the interior of each object. The OMGA is designed to be hardware-friendly, and can be implemented within two passes through the input document

Life cycle analysis in the printing industry: a review

Life Cycle Assessment (LCA) is the leading tool for estimating environmental effects of products and processes. Despite this wide use, LCA analysis remains problematic and limited. Within the printing industry, one of the primary problems is non-standardized assumptions and practices. This makes it difficult, if not impossible, to compare the life cycle impacts of products. This paper will compare LCA studies performed within the printing industry in order to identify common practices, limitations, areas for improvement, and opportunities for standardization. This comparison is focused on the data sources and methodologies used in the particular studies

Black-box printer models and their applications

In the electrophotographic printing process, the deposition of toner within the area of a given printer addressable pixel is strongly influenced by the values of its neighboring pixels. The interaction between neighboring pixels, which is commonly referred to as dot-gain, is complicated. The printer models which are developed according to a pre-designed test page can either be embedded in the halftoning algorithm, or used to predict the printed halftone image at the input to an algorithm being used to assess print quality. In our research, we examine the potential influence of a larger neighborhood (45?45) of the digital halftone image on the measured value of a printed pixel at the center of that neighborhood by introducing a feasible strategy for the contribution. We developed a series of six models with different accuracy and computational complexity to account for local neighborhood effects and the influence of a 45?45 neighborhood of pixels on the central printer-addressable pixel tone development. All these models are referred to as Black Box Model (BBM) since they are based solely on measuring what is on the printed page, and do not incorporate any information about the marking process itself. We developed two different types of printer models Standard Definition (SD) BBM and High Definition (HD) BBM with capture device Epson Expression 10000XL (Epson America, Inc., Long Beach, CA, USA) flatbed scanner operated at 2400 dpi under different analysis resolutions. The experiment results show that the larger neighborhood models yield a significant improvement in the accuracy of the prediction of the pixel values of the printed halftone image. The sample function generation black box model (SFG-BBM) is an extension of SD-BBM that adds the printing variation to the mean prediction to improve the prediction by more accurately matching the characteristics of the actual printed image. We also followed a structure similar to that used to develop our series of BBMs to develop a two-stage toner usage predictor for electrophotographic printers. We first obtained on a pixel-by-pixel basis, the predicted absorptance of printed and scanned page with the digital input using BBM. We then form a weighted sum of these predicted pixel values to predict overall toner usage on the printed page. Our two-stage predictor significantly outperforms existing method that is based on a simple pixel counting strategy, in terms of both accuracy and robustness of the prediction

Digital Image Segmentation and On–line Print Quality Diagnostics

During the electrophotographic (EP) process for a modern laser printer, object-oriented halftoning is sometimes used which renders an input raster page with different halftone screen frequencies according to an object map; this approach can reduce the print artifacts for the smooth areas as well as preserve the fine details of a page. Object map can be directly extracted from the page description language (PDL), but most of the time, it is not correctly generated. For the first part of this thesis, we introduce a new object generation algorithm that generates an object map from scratch purely based on a raster image. The algorithm is intended for ASIC application. To achieve hardware friendliness and memory efficiency, the algorithm only buffers two strips of an image at a time for processing. A novel two-pass connected component algorithm is designed that runs through all the pixels in raster order, collect features and classify components on the fly, and recycle unused components to save memories for future strips. The algorithm is finally implemented as a C program. For 10 test pages, with the similar quality of object maps generated, the number of connected components used can be reduced by over 97% on average compared to the classic two-pass connected component which buffers a whole page of pixels. The novelty of the connected component algorithm used here for document segmentation can also be potentially used for wide variety of other applications. The second part of the thesis proposes a new way to diagnose print quality. Compared to the traditional diagnostics of print quality which prints a specially designed test page to be examined by an expert or against a user manual, our proposed system could automatically diagnose a customer’s printer without any human interference. The system relies on scanning printouts from user’s printer. Print defects such as banding, streaking, etc. will be reflected on its scanned page and can be captured by comparing to its master image; the master image is the digitally generated original from which the page is printed. Once the print quality drops below a specified acceptance criteria level, the system can notify a user of the presence of print quality issues. Among so many print defects, color fading – caused by the low toner in the cartridge – is the focus of this work. Our image processing pipeline first uses a feature based image registration algorithm to align the scanned page with the master page spatially and then calculates the color difference of different color clusters between the scanned page and the master page. At last, it will predict which cartridge is depleted

Revision of the EU Green Public Procurement (GPP) Criteria for Imaging Equipment: Final Technical Report: Final criteria

This document is intended to provide the background information for the revision of the Green Public Procurement (GPP) criteria for Imaging Equipment. The study has been carried out by the Joint Research Centre's Directorate B (JRC Dir. B – Growth and Innovation) with technical support from a consulting consortium. The work is being developed for the European Commission's Directorate General for the Environment. EU GPP criteria aim at facilitating public authorities the purchase of products, services and works with reduced environmental impacts. The use of the criteria is voluntary. The criteria are formulated in such a way that they can be, if deemed appropriate by the individual authority, integrated into its tender documents. The main purpose of this technical report is to evaluate the current criteria and discuss if they are still relevant or should be revised, restructured or removed. It also identifies, based on the background technical analysis presented in the preliminary report , new criteria areas for consideration in order to better address key environmental impacts of the product group. Final version of the technical report includes final GPP criteria proposal.JRC.B.5-Circular Economy and Industrial Leadershi

Investigation of laser printing for 3D printing and additive manufacturing

Additive Manufacturing (AM), popularly called “3D printing,” has benefited from many two-dimensional (2D) printing technology developments, but has yet to fully exploit the potential of digital printing techniques. The very essence of AM is accurately forming individual layers and laminating them together. One of the best commercially proven methods for forming complex powder layers is laser printing, which has yet to be used to directly print three-dimensional (3D) objects above the microscale, despite significant endeavour. The core discovery of this PhD is that the electrostatic charge on toner particles, which enables the digital material patterning capabilities of 2D laser printing/photocopying, is disabling for building defect-free 3D objects after the manner attempted to date. Toner charge is not mostly neutralized with fusing as previously assumed. This work characterizes and substantiates the accumulation of residual toner charge as a primary cause for defects arising in 3D printed bodies. Next, various means are assessed to manage and neutralize residual toner charge. Finally, the complementary implementation of charge neutralization with electrostatic transfer methods is explored

Investigation of on-demand digital printing for the needs of Mine Safety Appliances co.

The printing needs of Mine Safety Appliances Co. (MSA) along with the definition and functions of ondemand digital printing seemed to be complimentary. Not only can digital presses improve turn around times, but they are also said to be economical for short print runs. Therefore, the focus of this study was to evaluate several on-demand digital printers and determine which press was most appropriate for MSA. After investigation, it was determined while no one press satisfied all of the areas, the Indigo Omnius met the most needs. The Omnius could save time and money printing bags, labels, and a variety of other packaging items. The Omnius, however, had some drawbacks. These drawbacks included not being able to print on both sides of a substrate and not having in-line finishing options. Also, the finishing options were quite costly to purchase separately. A cost analysis determined that the implementation of the Omnius at MSA was a project worth considering. However, further investigation beyond this thesis is recommended. This future investigation should focus on determining a better way to print manuals and evaluating whether or not options such as leasing or purchasing from a vendor that owns an Omnius, would be more beneficial to MSA than buying and implementing a press

Revision of EU Green Public Procurement (GPP) criteria for Imaging Equipment - Preliminary Report

Green Public Procurement (GPP), in which public authorities procure goods, services and works that have less environmental impact than comparable contracts, has the potential to accelerate the market introduction and uptake of less environmentally damaging technologies. This report forms the basis to revise the existing EU GPP criteria for Imaging Equipment. The revision of EU GPP criteria requires in-depth information about the technical and environmental performance of this product group as well as about the typical procurement processes. This report gathers the necessary background information for that and presents it in a structured form. The scientific body of evidence gathered will be crosschecked with sector-experienced stakeholders to find the best way to revise the criteria in order to deliver optimum environmental improvements while complying with Public Procurement law and safeguarding the Single Market.JRC.B.5-Circular Economy and Industrial Leadershi

Um método supervisionado para encontrar variáveis discriminantes na análise de problemas complexos : estudos de caso em segurança do Android e em atribuição de impressora fonte

Orientadores: Ricardo Dahab, Anderson de Rezende RochaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A solução de problemas onde muitos componentes atuam e interagem simultaneamente requer modelos de representação nem sempre tratáveis pelos métodos analíticos tradicionais. Embora em muitos caso se possa prever o resultado com excelente precisão através de algoritmos de aprendizagem de máquina, a interpretação do fenómeno requer o entendimento de quais são e em que proporção atuam as variáveis mais importantes do processo. Esta dissertação apresenta a aplicação de um método onde as variáveis discriminantes são identificadas através de um processo iterativo de ranqueamento ("ranking") por eliminação das que menos contribuem para o resultado, avaliando-se em cada etapa o impacto da redução de características nas métricas de acerto. O algoritmo de florestas de decisão ("Random Forest") é utilizado para a classificação e sua propriedade de importância das características ("Feature Importance") para o ranqueamento. Para a validação do método, dois trabalhos abordando sistemas complexos de natureza diferente foram realizados dando origem aos artigos aqui apresentados. O primeiro versa sobre a análise das relações entre programas maliciosos ("malware") e os recursos requisitados pelos mesmos dentro de um ecossistema de aplicações no sistema operacional Android. Para realizar esse estudo, foram capturados dados, estruturados segundo uma ontologia definida no próprio artigo (OntoPermEco), de 4.570 aplicações (2.150 malware, 2.420 benignas). O modelo complexo produziu um grafo com cerca de 55.000 nós e 120.000 arestas, o qual foi transformado usando-se a técnica de bolsa de grafos ("Bag Of Graphs") em vetores de características de cada aplicação com 8.950 elementos. Utilizando-se apenas os dados do manifesto atingiu-se com esse modelo 88% de acurácia e 91% de precisão na previsão do comportamento malicioso ou não de uma aplicação, e o método proposto foi capaz de identificar 24 características relevantes na classificação e identificação de famílias de malwares, correspondendo a 70 nós no grafo do ecosistema. O segundo artigo versa sobre a identificação de regiões em um documento impresso que contém informações relevantes na atribuição da impressora laser que o imprimiu. O método de identificação de variáveis discriminantes foi aplicado sobre vetores obtidos a partir do uso do descritor de texturas (CTGF-"Convolutional Texture Gradient Filter") sobre a imagem scaneada em 600 DPI de 1.200 documentos impressos em 10 impressoras. A acurácia e precisão médias obtidas no processo de atribuição foram de 95,6% e 93,9% respectivamente. Após a atribuição da impressora origem a cada documento, 8 das 10 impressoras permitiram a identificação de variáveis discriminantes associadas univocamente a cada uma delas, podendo-se então visualizar na imagem do documento as regiões de interesse para uma análise pericial. Os objetivos propostos foram atingidos mostrando-se a eficácia do método proposto na análise de dois problemas em áreas diferentes (segurança de aplicações e forense digital) com modelos complexos e estruturas de representação bastante diferentes, obtendo-se um modelo reduzido interpretável para ambas as situaçõesAbstract: Solving a problem where many components interact and affect results simultaneously requires models which sometimes are not treatable by traditional analytic methods. Although in many cases the result is predicted with excellent accuracy through machine learning algorithms, the interpretation of the phenomenon requires the understanding of how the most relevant variables contribute to the results. This dissertation presents an applied method where the discriminant variables are identified through an iterative ranking process. In each iteration, a classifier is trained and validated discarding variables that least contribute to the result and evaluating in each stage the impact of this reduction in the classification metrics. Classification uses the Random Forest algorithm, and the discarding decision applies using its feature importance property. The method handled two works approaching complex systems of different nature giving rise to the articles presented here. The first article deals with the analysis of the relations between \textit{malware} and the operating system resources requested by them within an ecosystem of Android applications. Data structured according to an ontology defined in the article (OntoPermEco) were captured to carry out this study from 4,570 applications (2,150 malware, 2,420 benign). The complex model produced a graph of about 55,000 nodes and 120,000 edges, which was transformed using the Bag of Graphs technique into feature vectors of each application with 8,950 elements. The work accomplished 88% of accuracy and 91% of precision in predicting malicious behavior (or not) for an application using only the data available in the application¿s manifest, and the proposed method was able to identify 24 relevant features corresponding to only 70 nodes of the entire ecosystem graph. The second article is about to identify regions in a printed document that contains information relevant to the attribution of the laser printer that printed it. The discriminant variable determination method achieved average accuracy and precision of 95.6% and 93.9% respectively in the source printer attribution using a dataset of 1,200 documents printed on ten printers. Feature vectors were obtained from the scanned image at 600 DPI applying the texture descriptor Convolutional Texture Gradient Filter (CTGF). After the assignment of the source printer to each document, eight of the ten printers allowed the identification of discriminant variables univocally associated to each one of them, and it was possible to visualize in document's image the regions of interest for expert analysis. The work in both articles accomplished the objective of reducing a complex system into an interpretable streamlined model demonstrating the effectiveness of the proposed method in the analysis of two problems in different areas (application security and digital forensics) with complex models and entirely different representation structuresMestradoCiência da ComputaçãoMestre em Ciência da Computaçã