Color laser printer forensic based on noisy feature and support vector machine classifier

Digital forensics in the ubiquitous era can enhance and protect the reliability of multimedia content where this content is accessed, manipulated, and distributed using high quality computer devices. Color laser printer forensics is a kind of digital forensics which identifies the printing source of color printed materials such as fine arts, money, and document and helps to catch a criminal. This paper present a new color laser printer forensic algorithm based on noisy texture analysis and support vector machine classifier that can detect which color laser printer was used to print the unknown images. Since each printer vender uses their own printing process, printed documents from different venders have a little invisible difference looks like noise. In our identification scheme, the invisible noises are estimated with the wiener-filter and the 2D Discrete Wavelet Transform (DWT) filter. Then, a gray level co-occurrence matrix (GLCM) is calculated to analyze the texture of the noise. From the GLCM, 384 statistical features are extracted and applied to train and test the support vector machine classifier for identifying the color laser printers. In the experiment, a total of 4,800 images from 8 color laser printer models were used, where half of the image is for training and the other half is for classification. Results prove that the presented algorithm performs well by achieving 99.3%, 97.4% and 88.7% accuracy for the brand, toner and model identification respectively.     

Printing 3D microfluidic chips with a 3D sugar printer

This study demonstrated how to quickly and effectively print two-dimensional (2D) and three-dimensional (3D) microfluidic chips with a low-cost 3D sugar printer. The sugar printer was modified from a desktop 3D printer by redesigning the extruder, so the melting sugar could be extruded with pneumatic driving. Sacrificial sugar lines were first printed on a base layer followed by casting polydimethylsiloxane (PDMS) onto the layer and repeating. Microchannels were then printed in the PDMS solvent, microfluidic chips dropped into hot water to dissolve the sugar lines after the PDMS was solidified, and the microfluidic chips did not need further sealing. Different types of sugar utilized for printing material were studied with results indicating that maltitol exhibited a stable flow property compared with other sugars such as caramel or sucrose. Low cost is a significant advantage of this type of sugar printer as the machine may be purchased for only approximately $800. Additionally, as demonstrated in this study, the printed 3D microfluidic chip is a useful tool utilized for cell culture, thus proving the 3D printer is a powerful tool for medical/biological research.     

Clean color: Improving multi‐filament 3D prints

Fused Filament Fabrication is an additive manufacturing process by which a 3D object is created from plastic filament. The filament is pushed through a hot nozzle where it melts. The nozzle deposits plastic layer after layer to create the final object. This process has been popularized by the RepRap community. Several printers feature multiple extruders, allowing objects to be formed from multiple materials or colors. The extruders are mounted side by side on the printer carriage. However, the print quality suffers when objects with color patterns are printed – a disappointment for designers interested in 3D printing their colored digital models. The most severe issue is the oozing of plastic from the idle extruders: Plastics of different colors bleed onto each other giving the surface a smudged aspect, excess strings oozing from the extruder deposit on the surface, and holes appear due to this missing plastic. Fixing this issue is difficult: increasing the printing speed reduces oozing but also degrades surface quality – on large prints the required speed level become impractical. Adding a physical mechanism increases cost and print time as extruders travel to a cleaning station. Instead, we rely on software and exploit degrees of freedom of the printing process. We introduce three techniques that complement each other in improving the print quality significantly. We first reduce the impact of oozing plastic by choosing a better azimuth angle for the printed part. We build a disposable rampart in close proximity of the part, giving the extruders the opportunity to wipe oozing strings and refill with hot plastic. We finally introduce a toolpath planner avoiding and hiding most of the defects due to oozing, and seamlessly integrating the rampart. We demonstrate our technique on several challenging multiple color prints, and show that our tool path planner improves the surface finish of single color prints as well.     

Appearance Sampling of Real Objects for Variable Illumination

The appearance of an object greatly changes under different lighting conditions. Even so, previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a linear subspace. A set of basis images spanning such a linear subspace can be obtained by applying the principal component analysis (PCA) for a large number of images taken under different lighting conditions. Since little is known about how to sample the appearance of an object in order to correctly obtain its basis images, it was a common practice to use as many input images as possible. In this study, we present a novel method for analytically obtaining a set of basis images of an object for varying illumination from input images of the object taken properly under a set of light sources, such as point light sources or extended light sources. Our proposed method incorporates the sampling theorem of spherical harmonics for determining a set of lighting directions to efficiently sample the appearance of an object. We further consider the issue of aliasing caused by insufficient sampling of the object's appearance. In particular, we investigate the effectiveness of using extended light sources for modeling the appearance of an object under varying illumination without suffering the aliasing caused by insufficient sampling of its appearance.     

基于Delphi的精确定位套打设计与实现

基于文本的套打方式以字符为计量单位,定位精度不高;而基于打印控制码的方式面向打印设备,编码繁琐且兼容差.Canvas提供了一个独立于设备的绘制图形对象的画布,通过将文本信息转化为图形对象输出,可实现更为精确的套打且兼容性强.描述了Delphi的普通文本和打印机控制码套打定位方式,引出了基于Canvas的精确套打程序设计与实现的原理、方法,并就实现的主要技术和相关API函数调用进行了分析.     

Deep learning-based optimal segmentation of 3D printed product for surface quality improvement and support structure reduction

Large-sized product cannot be printed as one piece by a 3D printer because of the volume limitation of most 3D printers. Some products with the complex structure and high surface quality should also not be printed into one piece to meet requirement of the printing quality. For increasing the surface quality and reducing support structure of 3D printed models, this paper proposes a 3D model segmentation method based on deep learning. Sub-graphs are generated by pre-segmenting 3D triangular mesh models to extract printing features. A data structure is proposed to design training data sets based on the sub-graphs with printing features of the original 3D model including surface quality, support structure and normal curvature. After training a Stacked Auto-encoder using the training set, a 3D model is pre-segmented to build an application set by the sub-graph data structure. The application set is applied by the trained deep-learning system to generate hidden features. An Affinity Propagation clustering method is introduced in combining hidden features and geometric information of the application set to segment a product model into several parts. In the case study, samples of 3D models are segmented by the proposed method, and then printed using a 3D printer for validating the performance.     

Clever Support: Efficient Support Structure Generation for Digital Fabrication

We introduce an optimization framework for the reduction of support structures required by 3D printers based on Fused Deposition Modeling (FDM) technology. The printers need to connect overhangs with the lower parts of the object or the ground in order to print them. Since the support material needs to be printed first and discarded later, optimizing its volume can lead to material and printing time savings. We present a novel, geometry‐based approach that minimizes the support material while providing sufficient support. Using our approach, the input 3D model is first oriented into a position with minimal area that requires support. Then the points in this area that require support are detected. For these points the supporting structure is progressively built while attempting to minimize the overall length of the support structure. The resulting structure has a tree‐like shape that effectively supports the overhangs. We have tested our algorithm on the MakerBot® Replicator? 2 printer and we compared our solution to the embedded software solution in this printer and to Autodesk® Meshmixer? software. Our solution reduced printing time by an average of 29.4% (ranging from 13.9% to 49.5%) and the amount of material by 40.5% (ranging from 24.5% to 68.1%).     

Path smoothing and feed rate planning for robotic curved layer additive manufacturing

Robotic curved layer additive manufacturing (a.k.a. multi-axis 3D printing) has been gaining attention recently owing to its simplicity and unique ability of printing complex shapes without using a support structure. However, as the printing path now is no long planar and the nozzle orientation is no longer fixed but changes continuously during printing, even though it could be smooth when defined in the workpiece coordinate system in both position and orientation of the nozzle, due to the inevitable numerical errors, it typically is unsmooth with many sharp-changing undulations when transformed to the coordinate system of the robot arm. As a result, the feed rate of printing has to be set extremely conservatively lest the printer would chatter or vibrate and seriously jeopardize the printing quality. In this paper, first, we present a practical B-spline based smoothing algorithm for removing sharp corners on the printing path while upholding the required cusp-height threshold on the printed surface. Next, for the smoothed printing path, we propose a feed rate scheduling strategy that will try to maximize the variable feed rate while subject to the kinematic constraints of the six joints of the robot arm. Both computer simulations and physical printing experiments are carried out to assess the proposed methodologies and the results give a positive confirmation on their advantages.     

A wavelet-based multi-dimensional temporal recurrent neural network for stencil printing performance prediction

The solder paste printing (SPP) is a critical procedure in a surface mount technology (SMT) based assembly line, which is one of the major attributes to the defect of the printed circuit boards (PCBs). The quality of SPP is influenced by multiple factors, such as the squeegee speed, pressure, the stencil separation speed, cleaning frequency, and cleaning profile. During printing, the printer environment is dynamically varying due to the physical change of solder paste, which can result in a dynamic variation of the relationships between the printing results and the influential factors. To reduce the printing defects, it is critical to understand such dynamic relationships. This research focuses on determining the printing performance during printing by implementing a wavelet filtering-based temporal recurrent neural network. To reduce the noise factor in the solder paste inspection (SPI) data, this research applies a three-dimensional dual-tree complex wavelet transformation for low-pass noise filtering and signal reconstruction. A recurrent neural network is utilized to model the performance prediction with low noise interference. Both printing sequence and process setting information are considered in the proposed recurrent network model. The proposed approach is validated using practical dataset and compared with other commonly used data mining approaches. The results show that the proposed wavelet-based multi-dimensional temporal recurrent neural network can effectively predict the printing process performance and can be a high potential approach in reducing the defects and controlling cleaning frequency. The proposed model is expected to advance the current research in the application of smart manufacturing in surface mount technology.     

Texture Mapping Real‐World Objects with Hydrographics

In the digital world, assigning arbitrary colors to an object is a simple operation thanks to texture mapping. However, in the real world, the same basic function of applying colors onto an object is far from trivial. One can specify colors during the fabrication process using a color 3D printer, but this does not apply to already existing objects. Paint and decals can be used during post‐fabrication, but they are challenging to apply on complex shapes. In this paper, we develop a method to enable texture mapping of physical objects, that is, we allow one to map an arbitrary color image onto a three‐dimensional object. Our approach builds upon hydrographics, a technique to transfer pigments printed on a sheet of polymer onto curved surfaces. We first describe a setup that makes the traditional water transfer printing process more accurate and consistent across prints. We then simulate the transfer process using a specialized parameterization to estimate the mapping between the planar color map and the object surface. We demonstrate that our approach enables the application of detailed color maps onto complex shapes such as 3D models of faces and anatomical casts.     

Automated quality control of printed flasks and bottles

The paper faces the quality control problem for printed flasks, bottles and cans, used as containers for drugs and beverages. The control is mainly aimed at identifying ink spots and faded prints produced by a serigraphic process, but the approach is generically applicable to any kind of printing and printed cylindrical surface. Differently from the existing systems, based on the acquisition of good printed samples, the automatic control is based on the original digital image feeded to the printing system. Therefore, the control takes place directly between the ideal model and the result of a complex printing process including a number of distortion and noise sources. Problems related to image acquisition, reconstruction and alignment are investigated; a novel technique for image-model verification, based on adaptive local deformation, is also proposed and tested over a significant set of samples. A complete prototype system designed for such quality control is finally described and its operating capability on the field is discussed.     

Automatic authentication of color laser print-outs using machine identification codes

Authentication of documents can be done by detecting the printing device used to generate the print-out. Many manufacturers of color laser printers and copiers designed their devices in a way to integrate a unique tracking pattern in each print-out. This pattern is used to identify the exact device the print-out originates from. In this paper, we present an important extension of our previous work for (a) detecting the class of printer that was used to generate a print-out, namely automatic methods for (b) comparing two base patterns from two different print-outs to verify if two print-outs come from the same printer and for (c) automatic decoding of the base pattern to extract the serial number and, if available, the time and the date the document was printed. Finally, we present (d) the first public dataset on tracking patterns (also called machine identification codes) containing 1,264 images from 132 different printers. Evaluation on this dataset resulted in accuracies of up to 93.0 % for detecting the printer class. Comparison and decoding of the tracking patterns achieved accuracies of 91.3 and 98.3 %, respectively.     

Optimizing Object Decomposition to Reduce Visual Artifacts in 3D Printing

We propose a method for the automatic segmentation of 3D objects into parts which can be individually 3D printed and then reassembled by preserving the visual quality of the final object. Our technique focuses on minimizing the surface affected by supports, decomposing the object into multiple parts whose printing orientation is automatically chosen. The segmentation reduces the visual impact on the fabricated model producing non-planar cuts that adapt to the object shape. This is performed by solving an optimization problem that balances the effects of supports and cuts, while trying to place both in occluded regions of the object surface. To assess the practical impact of the solution, we show a number of segmented, 3D printed and reassembled objects.     

Relating halftone dot quality to paper surface topography

Most printed material is produced by printing halftone dot patterns. One of the key issues that determine the attainable print quality is the structure of the paper surface, but the relation is non-deterministic in nature. We examine the halftone print quality and study the statistical dependence between the defects in printed dots and the topography measurement of the unprinted paper. The work concerns SC paper samples printed by an IGT gravure test printer. We have small-scale 2D measurements of the unprinted paper surface topography and the reflectance of the print result. The measurements before and after printing are aligned with subpixel resolution, and individual printed dots are detected. First, the quality of the printed dots is studied using Self Organizing Map and clustering and the properties of the corresponding areas in the unprinted topography are examined. The printed dots are divided into high and low print quality. Features from the unprinted paper surface topography are then used to classify the corresponding paper areas using Support Vector Machine classification. The results show that the topography of the paper can explain some of the print defects. However, there are many other factors that affect the print quality, and the topography alone is not adequate to predict the print quality.     

PackMerger: A 3D Print Volume Optimizer

We propose an optimization framework for 3D printing that seeks to save printing time and the support material required to print 3D shapes. Three‐dimensional printing technology is rapidly maturing and may revolutionize how we manufacture objects. The total cost of printing, however, is governed by numerous factors which include not only the price of the printer but also the amount of material and time to fabricate the shape. Our PackMerger framework converts the input 3D watertight mesh into a shell by hollowing its inner parts. The shell is then divided into segments. The location of splits is controlled based on several parameters, including the size of the connection areas or volume of each segment. The pieces are then tightly packed using optimization. The optimization attempts to minimize the amount of support material and the bounding box volume of the packed segments while keeping the number of segments minimal. The final packed configuration can be printed with substantial time and material savings, while also allowing printing of objects that would not fit into the printer volume. We have tested our system on three different printers and it shows a reduction of 5–30% of the printing time while simultaneously saving 15–65% of the support material. The optimization time was approximately 1 min. Once the segments are printed, they need to be assembled.     

Suitable properties of ink to create inkjet-printed surface-directed microchannels that utilize the pinning effect of a triple line on a rough surface

If microfluidic devices can be directly produced using printing techniques, the combination of microfluidics and printing techniques for other applications, such as printed electronics, will make all-printed highly-functionalized microfluidic devices possible. Therefore, we have made efforts to develop a technique for producing microfluidic devices using an inkjet printer. The microchannels that could be created using this technique were a kind of surface-directed channels that utilize the pinning effect of a triple line on a rough surface. In this study, we focused on what were the required properties of the printer ink during the wetting and drying processes of the ink. As a result, one of the properties required during the wetting process was that the advancing contact angle of the ink should be smaller than a certain value, which depended on the average volume of the ink drops ejected from the printhead and the number of drops per unit area. The receding contact angle should be smaller than about one third of each advancing angle. In addition, during the drying process, a small amount of surfactant added to the ink played a critical role in order to leave a continuous stain of the ink. As an application of this inkjet-printed channel, we also created a device for mixing aqueous solutions.     

基于非理想打印机模型的半色调化图像质量评价方法研究

胶印工艺中印刷的内容需要半色调化成二值图像。为了评价半色调化算法和图像的质量,就要对输出图像的设备建模。现有的建模方法都基于理想打印机,假定输出图像的像素和输出设备的一个矩形区域的状态对应。然而理想打印机反映不了实际胶印工艺中的像素点重叠、极小网点丢失、网点扩大等基本现象。本研究的目标是建立一个面向胶印工艺的打印机模型,用于半色调化图像质量评价算法的研究。     

Super‐high‐resolution transfer printing for full‐color OLED display patterning

Abstract— A transfer‐printing method for the patterning of thin polymer layers is described. A hard stamp with a raised feature is brought into contact with a spin‐coated organic film under elevated pressure and temperature to break the films. The patterned film is then transfer printed onto the devices. This method is used to print red/green/blue subpixel arrays with a pattern size as small as 12 μm at a resolution of 530 ppi to demonstrate its ability for full‐color organic light‐emitting‐display fabrication. Devices with printed organic layers have similar performance to spin‐coated controls under optimized printing temperature and pressure settings. The critical physical parameters include a soft intermediate plate for the sharp breaking of edge patterns, control of surface energies, and printing at moderate temperature and pressure to achieve intimate contact between the printed layer and the underlying substrate.     

STM32的环保型便携式3D打印机研制

本文以STM32F1系列32位微处理器作为主控芯片,混合式步进电机为XYZ三轴提供动力,构成小型便捷式3D打印机.该打印机可通过SD卡进行脱机离线打印,减少对主机的依赖,提高便携性,还配备了触摸屏控制功能,使控制界面更加简单明了,降低了操作失误的可能性;同时采用环保型材料PLA(Polylactic Acid,即聚乳酸),打印过程中不产生任何有害物质,打印产品可用于家庭、办公室等环境.     

利用喷墨打印技术制备的类神经气体传感器

利用喷墨打印技术沉积生物高分子溶液的方法,打印出金的梳状微电极的阵列图形,并采用NaX型沸石分子筛作为敏感膜,研制了探测神经类毒气沙林的相似物DMMP气体的阻抗型传感器。电极图形使用简单的绘图软件autoCAD画出,通过简单改进过的办公用喷墨打印机在金衬底上打印一层自组装膜的阻挡层,经过湿法刻蚀后得到了梳状微电极阵列。将制得的传感器对1ppm(即1×10-6)DMMP气体进行检测,测得在0.01Hz处,其电阻的相对变化值为10.7%。与传统MEMS工艺相比较,喷墨打印方法制备传感器具有工艺步骤简化,成本低,可在柔性等不同材料上制作等优点,有着广泛的应用前景。