Color Printing Research Articles

Study of print suitability of environment-friendly plastics using flexography printing

Environmental-friendly plastics (EFP) are new alternatives of fossil-based plastics. The EFP family mainly constitutes bio-plastics/bio-attributed plastics and post-consumer recycled plastics (PCR). EFP contributes around 10% of total plastics production in global plastic production. Presently EFP are mostly used in grocery bags, bin liners, compostable garbage bags and single-use plastics with single or spot color printing. Multi-color printing can add value or open new horizons for these materials, leading to high-value applications. It can also be used for high-speed printing or flexible packaging applications. Plastics available in this category come from both fossil-based and bio-based sources. Fossil-based bioplastics has almost similar degree of print suitability but materials coming from bio-based sources are yet to be explored for print suitability, especially with high-speed multi-color printing machines. Flexographic printing is known for high-quality and high-speed printing on different substrates, including paper, conventional plastics and fossil-based bio-plastics. The advantage of having a common impression cylinder (CIC) arrangement and the requirement of less pressure during printing makes it suitable for consideration for printing on EFP. Hence, this study, print suitability of EFP using flexography printing, is an attempt to explore the mutual compatibility of these substrates and printing process, which will prove to be a boon in the future for establishing EFP as a strong substitute for replacing conventional plastics.

Counterfeit Currency Detection

This paper presents a programmed framework designed to identify Indian currency notes and determine whether they are genuine or counterfeit. The system is of great utility in the banking sector and other fields. India has experienced an increase in counterfeit notes of denominations such as 100, 500, and 1000 rupees, attributed to advancements in technology such as scanning, color printing, and replication. This has led to a rise in counterfeit issues. The detection of counterfeit Indian currency notes is achieved through image processing techniques. Initially, image acquisition is performed, followed by preprocessing, including cropping, smoothing, and conversion to grayscale. Subsequently, image segmentation, feature extraction, reduction, and comparison are conducted. This framework can greatly aid in distinguishing genuine and counterfeit Indian currency notes, offering a valuable tool for various sectors, particularly in addressing the rising counterfeit issues

SOI Based metasurface for broadband perfect reflection in visible spectrum

We propose modeling and design of a low-loss all-dielectric metasurface (DM), comprised of Silicon on Insulator (SiO2) substrate to demonstrate a perfect reflector in the visible spectrum. The proposed metasurface unit cell consists of V and W shapes arranged in a mirror image configuration, with nanometre-sized gaps (g) between them. A narrow peak with a nearly 100% reflectance and a broad perfect reflectance spectrum is observed within the visible region (400–700 nm) of the electromagnetic spectrum. The effective electromagnetic parameters were also analyzed for electric and magnetic dipole resonance. The electric and magnetic field distributions at the resonant wavelength were also analyzed for the proposed structure. By altering the gap region ‘g’, the thickness of the dielectric Silica layer (ts ), and the Si resonator (t m), the proposed structure exhibits tunable characteristics. We have successfully illustrated the consistent position of the scattering parameter’s response, regardless of the structure’s rotation, concluding the homogeneity of the designed structure across the entire visible spectrum. The all-DM exhibits a unique combination of features, including a distinct and wide reflectance spectrum as well as a tuned and enhanced electric field which makes it an ideal platform for the applications in filters, color printing, low-loss slow-light devices, and nonlinear optics.

Release from response interference in color-word contingency learning

In identifying the print colors of words when some combinations of color and word occur more frequently than others, people quickly show evidence of learning these associations. This contingency learning effect is evident in faster and more accurate responses to high-contingency combinations than to low-contingency combinations. Across four experiments, we systematically varied the number of response-irrelevant word stimuli connected to response-relevant colors. In each experiment, one group experienced the typical contingency learning paradigm with three colors linked to three words; other groups saw more words (six or twelve) linked to the same three colors. All four experiments disconfirmed a central prediction derived from the Parallel Episodic Processing (PEP 2.0) model (Schmidt et al., 2016)—that the magnitude of the contingency learning effect should remain stable as more words are added to the response-irrelevant dimension, as long as the color-word contingency ratios are maintained. Responses to high-contingency items did slow down numerically as the number of words increased between groups, consistent with the prediction from PEP 2.0, but these changes were unreliable. Inconsistent with PEP 2.0, however, overall response time did not slow down and responses to low-contingency items actually sped up as the number of words increased across groups. These findings suggest that the PEP 2.0 model should be modified to incorporate response interference caused by high-probability associations when responding to low-probability combinations.

Water-Soluble Quantum Dots for Inkjet Printing Color Conversion Films with Simultaneous High Efficiency and Stability.

Water-soluble quantum dots (QDs) are necessary to prepare patterned pixels or films for high-resolution displays with less environmental burden but are very limited by the trade-off between photoluminescence and stability of QDs. In this work, we proposed synthesizing water-soluble QDs with simultaneous excellent luminescence properties and high stability by coating the amphiphilic poly(maleic anhydride-alt-1-octadecene)-ethanol amine (PMAO-EA) polymer on the surface of silane-treated QDs. These coated QDs show a photoluminescence quantum yield (PLQY) as high as 94%, and they have good photoluminescence stability against light irradiation and thermal attacks, owing to the suppression of the nonradiative recombination by the polymer layer and the isolation of oxygen and water by the silica layer. The water-soluble QDs, mixed with ethylene glycol, enable inkjet printing of QD color conversion films (QD-CCFs) with an average diameter of 68 μm for each pixel and a high PLQY of 91%. The QD-CCFs are demonstrated to fabricate red-emitting mini-LEDs by combining with blue mini-LED chips, which have an external quantum efficiency as high as 25.86% and a luminance of 2.44 × 107 cd/m2. We believe that the proposed strategy is applicable to other water-soluble QDs and paves an avenue for inkjet printing environmentally friendly QD-CCFs for mini/micro-LED displays.

Classification and selection of the main features for the identification of toxicity in Agaricus and Lepiota with machine learning algorithms.

The occurrence of fungi is cosmopolitan, and while some mushroom species are beneficial to human health, others can be toxic and cause illness problems. This study aimed to analyze the organoleptic, ecological, and morphological characteristics of a group of fungal specimens and identify the most significant features to develop models for fungal toxicity classification using genetic algorithms and LASSO regression. The results of the study indicated that odor, spore print color, and habitat were the most significant characteristics identified by the genetic algorithm GALGO. Meanwhile, odor, gill size, stalk shape, and twelve other features were the relevant characteristics identified by LASSO regression. The importance score of the odor variable was 99.99%, gill size obtained 73.7%, stalk shape scored 39.9%, and the remaining variables did not score higher than 18%. Logistic regression, k-nearest neighbor (KNN), and XG-Boost classification algorithms were used to develop models using the features selected by both GALGO and LASSO. The models were evaluated using sensitivity, specificity, and accuracy metrics. The models with the highest AUC values were XGBoost, with a maximum value of 0.99 using the features selected by LASSO, followed by KNN with a maximum value of 0.99. The GALGO selection resulted in a maximum AUC of 0.98 in KNN and XGBoost. The models developed in this study have the potential to aid in the accurate identification of toxic fungi, which can prevent health problems caused by their consumption.

Deep learning-assisted inverse design of metasurfaces for active color image tuning.

Metasurfaces, artificial planar nanostructures, offer numerous advantages for color printing applications, including ultra-high resolution, resistance to fading, wide color gamut coverage, and multifunctional capabilities. Due to the sensitivity of their resonance spectra to the external environment, metasurfaces have garnered significant interest for color tuning applications. However, most existing approaches are limited to passive color tuning, wherein only the color changes passively while the composite color image remains unaltered. Active color image tuning, on the other hand, requires precise matching of both color and intensity to the designed targets before and after the tuning process. In this study, we propose a novel approach for active metasurface color image tuning by modulating the environmental refractive index. Building upon a forward neural network that establishes the relationship between the metasurface geometric parameters and color/intensity information, we employ a multi-objective inverse adjoint neural network. This network not only overcomes the inherent 'one-to-many' problem in inverse design using neural networks but also facilitates active color image tuning under three distinct environmental conditions. Our work provides a new approach for the inverse design of metasurfaces and opens up possibilities for applications in dynamic color printing, information encryption, and other related fields.

Optical properties and applications of laser-induced disordered plasmonics metasurfaces

The lecture explores laser-induced plasmonic metasurfaces, focusing on their structural characteristics and optical properties. Despite their disordered nature, these metasurfaces excel in applications such as color printing, sensing, light manipulation, and energy harvesting, offering advantages over traditional ordered structures through detailed case studies.

Fake Currency Detection

Due to the great technological developments in the field of color printing in the past few years, it is becoming increasingly recognized that counterfeiting is a serious problem. It used to be possible and very simple for anyone to quickly prepare and print counterfeit currency notes using a computer and a laser printer at homes or places of employment. In the past, only printing houses had these facilities. The most crucial issue is now how to accurately distinguish fake currency from real currency using automatic machines. Almost all nations struggle greatly with the issue of counterfeit currency notes. But since counterfeiting has become such a pressing issue in India, it is thought to be the most serious issue there. Therefore, it is necessary to create a module that will aid in the quick and efficient recognition and detection of paper currency notes. An approach for the identification and verification of Indian currency is described in this proposed system. The authenticity of the currency will be verified using image processing methods, regardless of whether it is genuine.

Laser-ablated acoustofluidics-driven paper devices for controllable chemical engineering in color display applications

Paper-based analytical devices (PADs) have rapidly thrived in the last decade for their easy operation and rapid response. However, because of its low chemical reactivity, it’s still challenging to endow the paper substrate with more functions and expand its application field. Here, this work leverages lasers to do surface modifications of paper to raise its chemical reactivity. A gentle power of laser was utilized to ablate a part thickness of the paper. The effect of laser types was studied, including continuous-wave, nanosecond, and femtosecond lasers. Continuous-wave laser caused severe photothermal effects and produced more pyrolytic oil. The physical changes including mechanical strength and fluid wicking were studied. The chemical changes were analyzed by XPS and FTIR. Because of the produced aldehydes by laser ablation, the laser-modified papers were endowed with more functions and we experimented with aldehyde-related color reactions on them, which might promote the color printing industry. In addition, to fully exploit the produced aldehydes, our recently developed acoustofluidic PADs were employed for flow intensification and homogeneous mixing. This work demonstrates an economical and effective method for a new type of functional paper substrates which holds potential for various fields.

A Method of Enhancing Silk Digital Printing Color Prediction through Pix2Pix GAN-Based Approaches

Color prediction and color management for digital printed fabrics remain a challenging task. Accurate prediction of color appearances of digital printed fabrics would enable designers and manufacturers to better fulfill their design requirements and creative visions. We propose a color prediction method for silk digital printing utilizing a Pix2Pix Generative Adversarial Network (GAN) framework. This method aims to generate predicted images that possess the same stylistic and color characteristics as their actual fabrics after production. To develop and validate the method, color data and images are collected and processed from 5252 sets of paired original Pantone TPX color card and actual print sample fabrics. The results of this study demonstrate that the method can predict the colors of silk digital print samples while effectively reproducing the effects of inkjet printing in silk fabrics including silk crepe satin and silk twill. The method exhibits high prediction accuracy to an average CIEDE2000 value of 2.372 for silk crepe satin and 1.846 for silk twill. The findings of this research not only enhance the efficiency and accuracy of color management in fabric digital printing technology but also contribute to the exploration and development of high-fidelity color prediction techniques within the textile industry.

Detection Of Fake Bank Currency Using Machine Learning

Abstract: The development of colour printing technology has accelerated the production of counterfeit currency notes and their mass duplication. Counterfeiting of banknotes poses a significant threat to the financial system and undermines the integrity of currency .Image analysis to distinguish genuine banknotes from counterfeit ones based on distinctive features. Various image processing algorithms are then employed to extract key features, such as texture, colour, and security elements embedded in the banknotes. These features are crucial for differentiating authentic currency from counterfeit replicas .Machine learning algorithms, particularly deep neural networks, are employed to train a robust classification model using a labeled dataset containing examples of both genuine and fake banknotes. The model is designed to generalize well to unseen data, allowing for accurate detection of counterfeit currency across various denominations and designs. The proposed fake banknote detection system demonstrates promising results in terms of accuracy, speed, and scalability. It offers a reliable and efficient solution to financial institutions and law enforcement agencies for identifying counterfeit currency in real-time, thereby contributing to the preservation of the integrity of financial transactions and safeguarding the economy against illicit activities. Keywords:- KNN, SVM, Image Processing

Colorful 3D Printing: A Critical Feasibility Analysis of Multi-Wavelength Additive Manufacturing.

Employing two colors of light to 3D print objects holds potential for accessing advanced printing modes, such as the generation of multi-material objects from a single print. Thus, dual-wavelength-driven photoreactive systems (reactions that require or utilize two wavelengths) and their exploitation as chemo-technological solutions for additive manufacturing technologies have experienced considerable development over the last few years. Such systems saw an increase in printing speeds, a decrease in resolution thresholds, and─perhaps most importantly─the actual generation of multi-material objects. However, the pace at which such reactive systems are developed is moderate and varies significantly depending on the fashion in which the two colors of light are employed. Herein, we address for the first time the varying logic conjugations of light-activated chemical compounds in dual-wavelength photochemical processes in a systematic manner and consider their implications from a photochemical point of view. To date, four dual-wavelength reaction types have been reported, termed synergistic (λ1 AND λ2), antagonistic (reversed λ1 AND λ2), orthogonal (λ1 OR λ2), and─most recently─cooperative (λ1 AND λ2 or λ1 OR λ2). The progress of their implementation in additive manufacturing is assessed individually, and their concurrent and individual chemical challenges are identified. These challenges need to be addressed for future dual-wavelength photochemical systems to progress multi-wavelength additive manufacturing technologies beyond their current limitations.

Large area structural color printing based on dot-matrix laser interference patterning.

Optically Variable Devices (OVDs) are widely used as security features in anti-counterfeiting efforts. OVDs enable the display of color dynamic effects that are easily interpreted by the user. However, obtaining these elements over large areas poses certain challenges in terms of efficiency. The paper presents a modified approach for manufacturing plasmonic type OVDs through dot-matrix technology, which is a standard origination step of security holograms. By adjusting the spatial filters in the optical scheme, it is possible to double the resolution of the recorded quasi-sinusoidal diffraction gratings. The experiments confirm the creation of diffraction gratings with frequencies from 1600 to 3500 lines per mm, which facilitates the production of plasmonic zero-order spectral filters. The paper shows how the transmission characteristics of the studied elements are affected by the geometric parameters of the diffraction grating, silver layer thickness, angle of incidence, and polarization of light. The results have shown that using the proposed method it is possible to obtain 1D or 2D structural color OVD-image on a large area - several square centimeters and more. High speed recording of such elements is provided: the exposure time was from 120 to 400 ms depending on the grating resolution for a 0.05 mm2 frame, the total printing time for the size of the 25×25 mm2 OVD was about 2.5 hours for a 1D element, and less than 3.5 hours for a 2D element. Thus, the proposed method and the OVD elements produced by it can be useful to designers of optical security elements as a simpler and faster alternative to electron-beam lithographic technologies.

Multicoloured Jacquard Artworks Reproduction with C, M, Y, and K Channels Modification to Improve Weave Colour Accuracy

Multi-coloured Jacquard artwork reproduction has been restricted by the modern setting of weaving machinery. To resolve the current limitations, innovative weaving applications have been introduced. The subtractive CMYK system used for colour printing has been employed for multi weave colour reproduction as a wide scope of a weave colour creation is possible by utilizing a small number of weft yarn colours. In use of cyan [C], magenta [M] and yellow [Y] coloured yarns, a range of CMYK secondary colours (red [R], green [G] and blue [B]) production is feasible by juxtaposing a pair of the three yarn colours. In addition, controlling chroma levels of the primary colours is viable by mixing with a black yarn. However, there are variations between CMYK colour mixing and optical yarn colour mixing due to the material differences. Therefore, modifications of the [C], [M], and [Y] colour channels are required to reproduce tertiary colours such as a black colour. This is because opaque and non-blendable yarns are used to create weave colours and therefore, exhibited yarn colours are all perceived together. In use of image processing tools offered by Adobe Photoshop, a pair of the [C], [M], [Y], and [K] colour channels are merged to individually generate the primary ([C], [M], [Y]) and secondary ([R], [G] and [B]) colour channels. In the process, a pair of C, M, Y and K channels is combined based on mathematical functions. As a result, new six colour channels ([C], [M], [Y], [R], [G], and [B]) are created to improve weave colour reproduction accuracy. This study introduces details of the colours segmentation processes and weaving experiment results that examines the significance of the newly developed the colour channels for multi-coloured artwork reproduction.

Digital Color Output Conformity to ISO12647-7 Standards (GRACoL 2013 [CGATS21-2-CRPC6]) With the Use of Statistical Process Control (SPC)

The purpose of this applied research was to apply the statistical process control (SPC) to determine the digital color output conformity to ISO12647-7 standards in a color managed digital printing workflow (CMDPW) over a period of 100 days (N=100). The quality of digital color printing is determined by these influential factors: screening method applied, type of printing process, calibration method, device profile, ink (dry toner or liquid toner), printer resolution, and the substrate (paper). For this research, only the color printing attribute overall average color deviation (ACD; ΔE(2000)) was analyzed to examine the CMDPW process consistency in a day-to-day digital printing operation. Printed colors from the random sample size (n=80) were measured against the General Requirement for the Applications in the Commercial Offset Lithography (GRACoL 2013) standards to derive the colorimetric/densitometric values. Reference colorimetric values used in the analysis were the threshold deviations (acceptable color deviations) as outlined in the ISO12647-7 standards (GRACoL 2013). A control chart analysis was applied for further determining the process (CMDPW) ACD variation. The data collected were run through multiple software applications (Microsoft Excel/SPSS/Minitab) to apply various statistical methods. Analyzed data from the experiment revealed that the printed colorimetric values were in match (aligned) with the GRACoL 2013 (reference/target) standards. Since the color values were in control throughout the process, this enabled the CMDPW to produce consistent acceptable color deviation (average printed ΔE(2000)=2.978). (The acceptable threshold color deviation is ΔE(2000)≤3.00.)

An Application of Deep Learning Technology in The Recognition of Forged Documents with Color Laser Printing

<p>Advanced laser printing technology is now widely used in daily life and at work. Because laser printers are so easy to obtain and use, they have also become a popular method for criminals to forge important documents like currency, securities, and certificates. To obtain evidence for document forgery, traditional forensics use chemical analysis of ink, but the cost is high. Laser color printing uses halftone technology. This technology combines the CMYK printing colors’ halftone screens at their respective angles. When correctly superimposed, they will form a moiré pattern. And the moiré pattern of a color block differs depending on the printer brand or model. This paper will use deep learning to create an image recognition model that can quickly classify forged documents by combining image processing, data augmentation, and transfer learning. The experimental results are examined using indicators of accuracy, precision, recall, F1-score, and PR curve. The results show that ResNet-50 has the best performance and can be used to detect document forgery. The study’s findings will be useful for future criminal investigators and forensic personnel in their work.</p> <p> </p>

Print consistency evaluation on uncoated paper using various digital print engines

Print quality is most exclusively aspect which is observed mostly and corelated to different printing attributes. Various attributes like print density, color difference (ΔE value) and overprint trap are some crucial aspects to evaluate print quality. Print density refers thickness of ink film applied on any media, color difference provides significant mismatch between targeted and printed while evaluating print quality and overprint trap is ability to accept subsequent layer of ink on already printed ink. This research emphasizes on study of print quality and evaluation in terms of print consistency on uncoated paper using various digital print engines

Handbook of the Colour Print in China, 1600–1800, edited by Anne Farrer and Kevin McLoughlin

Handbook of the Colour Print in China, 1600–1800, edited by Anne Farrer and Kevin McLoughlin

Design and characterization of color printed polyurethane films as biomedical phantom layers.

We propose a new, user-friendly and accessible approach for fabricating thin phantoms with controllable absorption properties in magnitude, spectral shape, and spatial distribution. We utilize a standard office laser color printer to print on polyurethane thin films (40 - 60 μm), commonly available as medical film dressings and ultrasound probe covers. We demonstrate that the optical attenuation and absorption of the printed films correlate linearly with the printer input settings (opacity), which facilitates a systematic phantom design. The optical and acoustic properties of these polyurethane films are similar to biological tissue. We argue that these thin phantoms are applicable to a wide range of biomedical applications. Here, we introduce two potential applications: (1) homogeneous epidermal melanin phantoms and (2) spatially resolved absorbers for photoacoustic imaging. We characterize the thin phantoms in terms of optical properties, thickness, microscopic structure, and reproducibility of the printing process.