Printed Color Images Research Articles

Large-scale high purity and brightness structural color generation in layered thin film structures via coupled cavity resonance

Abstract Structural colors, resulting from the interaction of light with nanostructured materials rather than pigments, present a promising avenue for diverse applications ranging from ink-free printing to optical anti-counterfeiting. Achieving structural colors with high purity and brightness over large areas and at low costs is beneficial for many practical applications, but still remains a challenge for current designs. Here, we introduce a novel approach to realizing large-scale structural colors in layered thin film structures that are characterized by both high brightness and purity. Unlike conventional designs relying on single Fabry–Pérot cavity resonance, our method leverages coupled resonance between adjacent cavities to achieve sharp and intense transmission peaks with significantly suppressed sideband intensity. We demonstrate this approach by designing and experimentally validating transmission-type red, green, and blue colors using an Ag/SiO2/Ag/SiO2/Ag configuration on fused silica substrate. The measured spectra exhibit narrow resonant linewidths (full width at half maximum ∼60 nm), high peak efficiencies (>40 %), and well-suppressed sideband intensities (∼0 %). In addition, the generated color can be easily tuned by adjusting the thickness of SiO2 layer, and the associated color gamut coverage shows a wider range than many existing standards. Moreover, the proposed design method is versatile and compatible with various choices of dielectric and metallic layers. For instance, we demonstrate the production of angle-robust structural colors by utilizing high-index Ta2O5 as the dielectric layer. Finally, we showcase a series of printed color images based on the proposed structures. The coupled-cavity-resonance architecture presented here successfully mitigates the trade-off between color brightness and purity in conventional layered thin film structures and provides a novel and cost-effective route towards the realization of large-scale and high-performance structural colors.

RGB‐Color Textile‐Based Flexible and Transparent OLEDs Considering Aesthetics

AbstractRecently, as state‐of‐the‐art displays, wearable electronic devices and free‐form displays have begun to attract attention to the point that much research on textile‐based displays has been actively conducted as an ultimate platform for wearable displays. However, although many studies have reported organic light‐emitting diodes (OLEDs) as the most suitable type for textile‐based displays due to their high opto‐electronic performance and flexibility, most research on textile‐based OLEDs (textile OLEDs) has left for the future improvements that require the use of transparent OLEDs (trOLEDs) for applications where aesthetics are important, such as fashion displays and automobile interiors. Herein, RGB‐color trOLEDs are designed using a dielectric‐metal‐dielectric transparent electrode to overcome the limitations of previous works on textile‐based non‐transparent OLEDs and to improve the aesthetic elements of textile displays. The opto‐electronic performance and the mechanical characteristics of textile RGB trOLEDs are analyzed, and specifically, this study suggests a new method and a novel equation for an optical analysis to quantify the clarity of printed color images (i.e., information) on a textile substrate when trOLEDs on the textile substrate are not operated, as needed to optimize and maximize the aesthetic elements of textile displays.

Predicting Laser-Induced Colors of Random Plasmonic Metasurfaces and Optimizing Image Multiplexing Using Deep Learning.

Structural colors of plasmonic metasurfaces have been promised to a strong technological impact thanks to their high brightness, durability, and dichroic properties. However, fabricating metasurfaces whose spatial distribution must be customized at each implementation and over large areas is still a challenge. Since the demonstration of printed image multiplexing on quasi-random plasmonic metasurfaces, laser processing appears as a promising technology to reach the right level of accuracy and versatility. The main limit comes from the absence of physical models to predict the optical properties that can emerge from the laser processing of metasurfaces in which random metallic nanostructures are characterized by their statistical properties. Here, we demonstrate that deep neural networks trained from experimental data can predict the spectra and colors of laser-induced plasmonic metasurfaces in various observation modes. With thousands of experimental data, produced in a rapid and efficient way, the training accuracy is better than the perceptual just noticeable change. This accuracy enables the use of the predicted continuous color charts to find solutions for printing multiplexed images. Our deep learning approach is validated by an experimental demonstration of laser-induced two-image multiplexing. This approach greatly improves the performance of the laser-processing technology for both printing color images and finding optimized parameters for multiplexing. The article also provides a simple mining algorithm for implementing multiplexing with multiple observation modes and colors from any printing technology. This study can improve the optimization of laser processes for high-end applications in security, entertainment, or data storage.

Direct laser printing color images based on the microstructure modulation of phase change material

Multi-color generation based on phase-change material recently has attracted much interest due to its potential applications in color printing, displays and data visualization domains. In this work, a simple thin-film stack design is reported, namely “ZnS-SiO2/Ge2Sb2Te5/glass substrate”. The influence of microstructure (i.e. crystallization and bumps) on the reflectivity spectra is investigated via the developed model. Moreover, experimental results are in basically agreement with the simulations. Thus, multiple colors can be obtained via tailoring microstructure of the stacked thin films induced by laser irradiations. In this case, various color images are printed on the designed thin-film stack, which has potential applications in color printing aspect, etc.

Authenticity and copyright verification of printed images

Perceptual image hashing and digital watermarking are two of the extensively investigated techniques for content authentication and copyright verification of digital images, respectively. One of the significant challenges of perceptual image hashing is a better tradeoff between robustness and discrimination. On the other hand, a major objective of digital watermarking techniques is to provide enhanced robustness and imperceptibility. In this paper, we present extensive experimental analysis, detailed laboratory forensic investigations, and application of the wave atom transform (WAT) based perceptual image hashing and digital watermarking techniques for printed images. Authenticity and copyright of printed images are verified via image hashing and digital watermarking techniques which are resilient against print-scan process distortions. To fulfill the requirement of a good balance between print-scan robustness and discrimination capabilities, we propose a compact, hybrid image hash using lower and middle frequency scale bands in the wave atom coefficients tiling. The hybrid image hash generation strategy is also advantageous due to its computational simplicity and reduced size of the hash value. Furthermore, we propose an enhanced multipurpose scheme which can support multiple applications, such as image authentication and copyright protection, simultaneously, for both digital-only and print-scanned images. Experimental analysis demonstrates the ability of wave atom based image hashing and watermarking schemes to provide authenticity and copyright verification for printed color images.

295 Validation of a Cytotechnologist Manual Counting Service for the Ki67 Index in Neuroendocrine Tumors of the Pancreas and Gastrointestinal Tract

Pathologists routinely assess Ki67 immunohistochemistry to grade gastrointestinal and pancreatic neuroendocrine tumors. Unfortunately, manual counts of the Ki67 index are very time consuming, and “eyeball estimation” has been criticized for being unreliable. Manual Ki67 counts performed by cytotechnologists could potentially save pathologist time and improve accuracy. To assess the concordance between manual Ki67 index counts performed by cytotechnologists vs eyeball estimates and manual Ki67 counts by pathologists. Ki67 immunohistochemical stains were retrieved from archived gastrointestinal or pancreatic neuroendocrine tumor resections. We compared pathologist Ki67 eyeball estimates on glass slides and printed color images with manual counts by three cytotechnologists and gold standard manual Ki67 index counts by three pathologists. Tumor grade agreement between pathologist image eyeball estimate and gold standard pathologist manual count was fair (K value of 0.31 [95% CI 0.03–0.60]). In nine of 20 cases (45%), the mean pathologist eyeball estimate was one grade higher than the mean pathologist manual count. There was almost perfect agreement in classifying tumor grade between the mean cytotechnologist manual count and the mean pathologist manual count (K value of 0.91 [95% CI 0.7–1.0]). In 20 cases, there was only one grade disagreement between the two methods. Eyeball estimation by pathologists required less than one minute, while manual counts by pathologists required a mean of 17 minutes per case. Eyeball estimation of the Ki67 index has a high rate of tumor grade misclassification compared to manual counting. Cytotechnologist manual counts are accurate and save pathologists time.

Validation of a Cytotechnologist Manual Counting Service for the Ki67 Index in Neuroendocrine Tumors of the Pancreas and Gastrointestinal Tract.

- Pathologists routinely assess Ki67 immunohistochemistry to grade gastrointestinal and pancreatic neuroendocrine tumors. Unfortunately, manual counts of the Ki67 index are very time consuming and eyeball estimation has been criticized as unreliable. Manual Ki67 counts performed by cytotechnologists could potentially save pathologist time and improve accuracy. - To assess the concordance between manual Ki67 index counts performed by cytotechnologists versus eyeball estimates and manual Ki67 counts by pathologists. - One Ki67 immunohistochemical stain was retrieved from each of 18 archived gastrointestinal or pancreatic neuroendocrine tumor resections. We compared pathologists' Ki67 eyeball estimates on glass slides and printed color images with manual counts performed by 3 cytotechnologists and gold standard manual Ki67 index counts by 3 pathologists. - Tumor grade agreement between pathologist image eyeball estimate and gold standard pathologist manual count was fair (κ = 0.31; 95% CI, 0.030-0.60). In 9 of 20 cases (45%), the mean pathologist eyeball estimate was 1 grade higher than the mean pathologist manual count. There was almost perfect agreement in classifying tumor grade between the mean cytotechnologist manual count and the mean pathologist manual count (κ = 0.910; 95% CI, 0.697-1.00). In 20 cases, there was only 1 grade disagreement between the 2 methods. Eyeball estimation by pathologists required less than 1 minute, whereas manual counts by pathologists required a mean of 17 minutes per case. - Eyeball estimation of the Ki67 index has a high rate of tumor grade misclassification compared with manual counting. Cytotechnologist manual counts are accurate and save pathologist time.

Inkjet Color Printing by Interference Nanostructures.

Color printing technology is developing rapidly; in less than 40 years, it moved from dot matrix printers with an ink-soaked cloth ribbon to 3D printers used to make three-dimensional color objects. Nevertheless, what remained unchanged over this time is the fact that in each case, dye inks (CMYK or RGB color schemes) were exclusively used for coloring, which inevitably limits the technological possibilities and color reproduction. As a next step in printing color images and storing information, we propose the technology of producing optical nanostructures. In this paper, we report use of inkjet technology to create colored interference layers with high accuracy without the need for high-temperature fixing. This was made possible due to using titania-based colloidal ink yielding monolithic coatings with a high refractive index (2.00 ± 0.08 over the entire visible range) when naturally dried. By controlling the film thickness by using inkjet deposition, we produced images based on controlled interference and implementing color printing with one ink. The lack of dyes in the proposed method has good environmental prospects, because applied systems based on a crystalline anatase sol are nontoxic and biologically inert. The paper explains in detail the principle of producing interference images by the classical inkjet method and shows the advantages of this technique in depositing coatings with uniform thickness, which are required for large-scale interference color imaging even on unprepared polymer films. This article demonstrates the possibility of inkjet printing of nanostructures with a precision in thickness of up to 50 nm, we believe that the proposed approach will be the groundwork for developing interference color printing approach and allow to implement new methods of forming optical nano-objects by widely available techniques.

Recovering neugebauer colorant reflectances and Ink‐spreading curves from printed color images

Spectral reflection prediction models, although effective, are impractical for certain industrial applications such as self‐calibrating devices and online monitoring because their calibration requires specific color‐constant calibration patches. Using the CMYK Ink‐Spreading enhanced Yule‐Nielsen‐modified Spectral Neugebauer model (IS‐YNSN), we propose a method to recover the colorant reflectances (Neugebauer primaries), the ink‐spreading curves, and the Yule‐Nielsen n‐value using only tiles extracted from printed color images. There is no prior knowledge about the reproduction device. Thanks to a set of constraints based on principal component analysis and the relationships between composed Neugebauer primaries and the ink transmittances, good approximations of the Neugebauer primaries are achieved. These approximations are then optimized, yielding an accurately calibrated IS‐YNSN model comparable to the one obtained by classical calibrations. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 216–233, 2014; Published online 23 February 2013 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/col.21800

Information Hiding for “Color to Gray and back” with Hartley, Slant and Kekre’s wavelet using Normalization

The paper shows performance comparison of three proposed methods with orthogonal wavelet alias Hartley,Slant &Kekres wavelet using Normalization for Color to Gray and Back. The color information of the image is embedded into its intermediate gray scale version with wavelet using normalization method. Instead of using the original color image for storage and transmission, intermediate gray image (Gray scale version with embedded color information) can be used, resulting into better bandwidth or storage utilization. Among three algorithms considered the second algorithm give better performance as compared to first and third algorithm. In our experimental results second algorithm for Kekres wavelet using Normalization gives better performance in Color to gray and Back w.r.t all other wavelet transforms in method 1, method 2 and method 3. The intent is to achieve compression of 1/3 and to print color images with black and white printers and to be able to recover the color information. Keywords-Color Embedding, Color-to-Gray Conversion, Transforms, Wavelets,Normalization ,Compression.

Color to Gray and back’ using normalization of color components with Cosine, Haar and Walsh Wavelet

The paper shows performance comparison of three proposed methods with orthogonal wavelet alias Cosine, Haar & Walsh wavelet using Normalization for 'Color to Gray and Back'. The color information of the image is embedded into its gray scale version using wavelet and normalization method. Instead of using the original color image for storage and transmission, gray image (Gray scale version with embedded color information) can be used, resulting into better bandwidth or storage utilization. Among three algorithms considered the second algorithm give better performance as compared to first and third algorithm. In our experimental results second algorithm for DCT wavelet using Normalization gives better performance in 'Color to gray and Back' w.r.t all other wavelet transforms in method 1, method 2 and method 3. The intent is to achieve compression of 1/3 and to print color images with black and white printers and to be able to recover the color information as and when required. Keywords- Color Embedding, Color-to-Gray Conversion, Transforms, Wavelets Normalization , Compression.

Research on the Imaging Mechanism of Additive Color of Fluorescent Ink-Jet Ink

The formation of color images are generally divided into two methods: additive color imaging based on color light mixture and subtractive color imaging based on colorant mixture. Additive color imaging refers to the color image mixed by a certain percentage of the three primary color lights: red (R), green (G) and blue (B), such as LED display, cell phone screens, digital cameras and others. Subtractive color imaging refers to the color image generated by light mixture reflected by each colorant, due to some light of different wavelength in the white light separately absorbed by certain colorant after mixing a certain percentage of the three primary colorant: cyan (C), magenta (M) and yellow (Y). Inkjet, color laser printing, inkjet printing, etc. belong to the subtractive color imaging. Most commonly, printing also belongs to the subtractive color imaging. This thesis is based on the characteristics that fluorescent materials can produce colors under UV excitation, designing and preparing three fluorescent inkjet inks which can respectively produce red (R), green (G), blue (B) under UV light excitation, using inkjet printers to print color images, investigating the imaging mechanism of the additive color based on fluorescence inkjet printing, and observing the imaging results. The results show that color effect of monochrome image is good, and the color deviation is large after overlapping different colors.

Calibrating ink spreading curves by optimal selection of tiles from printed color images

The Yule-Nielsen modified spectral Neugebauer model (YNSN) enables predicting reflectance spectra from ink surface coverages of halftones. In order to provide an improved prediction accuracy, this model is enhanced with an ink spreading model accounting for ink spreading in all superposition conditions (IS-YNSN). As any other spectral reflection prediction model, the IS-YNSN model is conceived to predict the reflection spectra of color-constant patches. Instead of color-constant patches, we investigate if tiles located within color images can be accurately predicted and how they can be used to facilitate the calibration of the ink spreading model. In the present contribution, we detail an algorithm to automatically select image tiles as uniform as possible from color images by relying on their CMY or CMYK pixel values. The tile selection algorithm incorporates additional constraints relying on surface coverages of the inks. We demonstrate that an ink spreading model calibrated with as few as 5 to 10 optimally chosen image tiles allows the corresponding YNSN model to provide accurate spectral predictions.

Calibrating ink spreading curves by optimal selection of tiles from printed color images

Calibrating ink spreading curves by optimal selection of tiles from printed color images

Color to Gray: Visual Cue Preservation

Both commercial and scientific applications often need to transform color images into gray-scale images, e.g., to reduce the publication cost in printing color images or to help color blind people see visual cues of color images. However, conventional color to gray algorithms are not ready for practical applications because they encounter the following problems: 1) Visual cues are not well defined so it is unclear how to preserve important cues in the transformed gray-scale images; 2) some algorithms have extremely high time cost for computation; and 3) some require human-computer interactions to have a reasonable transformation. To solve or at least reduce these problems, we propose a new algorithm based on a probabilistic graphical model with the assumption that the image is defined over a Markov random field. Thus, color to gray procedure can be regarded as a labeling process to preserve the newly well--defined visual cues of a color image in the transformed gray-scale image. Visual cues are measurements that can be extracted from a color image by a perceiver. They indicate the state of some properties of the image that the perceiver is interested in perceiving. Different people may perceive different cues from the same color image and three cues are defined in this paper, namely, color spatial consistency, image structure information, and color channel perception priority. We cast color to gray as a visual cue preservation procedure based on a probabilistic graphical model and optimize the model based on an integral minimization problem. We apply the new algorithm to both natural color images and artificial pictures, and demonstrate that the proposed approach outperforms representative conventional algorithms in terms of effectiveness and efficiency. In addition, it requires no human-computer interactions.

Constrained Acquisition of Ink Spreading Curves From Printed Color Images

Today's spectral reflection prediction models are able to predict the reflection spectra of printed color images with an accuracy as high as the reproduction variability allows. However, to calibrate such models, special uniform calibration patches need to be printed. These calibration patches use space and have to be removed from the final product. The present contribution shows how to deduce the ink spreading behavior of the color halftones from spectral reflectances acquired within printed color images. Image tiles of a color as uniform as possible are selected within the printed images. The ink spreading behavior is fitted by relying on the spectral reflectances of the selected image tiles. A relevance metric specifies the impact of each ink spreading curve on the selected image tiles. These relevance metrics are used to constrain the corresponding ink spreading curves. Experiments performed on an inkjet printer demonstrate that the new constraint-based calibration of the spectral reflection prediction model performs well when predicting color halftones significantly different from the selected image tiles. For some prints, the proposed image based model calibration is more accurate than a classical calibration.

이산 웨이블릿 변환과 명암도 동시발생 행렬을 이용한 컬러 레이저프린터 판별 알고리즘

고성능 저가의 디지털 인쇄기기의 출현으로 불법적인 위변조가 사회적인 문제로 대두되고 있고, 이를 해결하기 위해서 디지털 포렌식 기술이 필수적이다. 본 논문에서는 컬러 디지털 인쇄기기를 판별하기 위한 디지털 포렌식 기술을 제안한다. 컬러 디지털 인쇄기기는 제조사마다 인쇄방법이 다르기 때문에, 출력물에 작은 차이가 존재한다. 이와 같은 차이점을 활용하면, 임의의 주어진 출력물에 대해 어떠한 인쇄기기로 출력되었는지 구별이 가능하다. 제안하는 방법에서는 차이점을 구별하기 위하여 출력물을 스캔한 디지털 이미지에 대해 이산 웨이블릿 변환을 수행하여 계산한 고주파 영역을 추출한다. 이에 대해 명암도 동시발생 행렬을 계산한 후에 행렬 데이터의 표준편차, 첨도, 왜도, 공분산, 상관계수의 특징을 추출하였다. 추출된 특징을 서포트 벡터 머신 분류기에 적용하여 디지털 인쇄기기를 판별하였다. 제안한 알고리즘의 성능을 분석하기 위하여 총 2,597장 이미지와 7대 프린터(HP, Canon, Xerox DCC400, Xerox DCC450, Xerox DCC5560, Xerox DCC6540, Konica)를 가지고, 기존 알고리즘과 비교 분석하였다. 그 결과에 따르면 제안한 알고리즘은 컬러 디지털 인쇄기기를 판별하는데 있어서 평균 96.9% 정확률을 보였다. High-quality and low-price digital printing devices are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. Since different printer companies use different manufactural systems, printed documents from different printers have little difference in visual. Analyzing this artifact, we can identify the color laser printers. First, high-frequency components of images are extracted from original images with discrete wavelet transform. After calculating the gray-level co-occurrence matrix of the components, we extract some statistical features. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, total 2,597 images of 7 printers (HP, Canon, Xerox DCC400, Xerox DCC450, Xerox DCC5560, Xerox DCC6540, Konica), are tested to classify the color laser printer. The results prove that the presented identification method performs well with 96.9% accuracy.

Optimization of Cartridge Life Using JND Sampling Without Compromising the Visual Quality of Printed Images

This paper presents an innovative pre-dithering or prehalftoning approach of sampling CMY color space using nonlinear sampling of RGB space, under physiological limitations of human color vision. The certified sound color vision human eye color intensity thresholds have been computed in terms of Just Noticeable Differences (JNDs) in each basic color and then used for sampling the color images to be printed. From our findings of color image sampling work, we propose that the existing 22 level quantized ink injection system is inadequate to represent color images with minimum loss of visual information. So we propose an injection system with 24, 26 and 28 levels in Cyan, Magenta and Yellow respectively. The proposed system minimizes the utilization of color inks without affecting visual quality of printed color images on white background. The proposed scheme is effective for printing the dark colors, on the other hand it generates false contours while printing the light colors, as already discussed in published literature. Experimentation has been carried out to estimate the ‘Threshold of Lightness’ of colors in RGB space. Using the decided threshold of lightness, if the proposed scheme is applied only to dark colors, considerable saving of color ink can be achieved. This technique considerably reduces the consumption of expensive color inks for printing color images on white background and enhances the cartridge life, reducing the cost of inkjet printing.

Deducing Ink Spreading Curves from Reflection Spectra Acquired Within Printed Color Images

The Yule-Nielsen modified spectral Neugebauer model (YNSN) enhanced for accounting for ink spreading in the different ink superposition conditions provides accurate spectral predictions, but requires one to measure the reflectances of special halftone calibration patches in order to compute the ink spreading curves mapping nominal ink surface coverage to effective ink surface cov- erage. Printing special halftone calibration patches within the bor- ders of the print pages is cumbersome, since these special patches need to be cut out before assembling the final printed product. In the present contribution, we calibrate the ink spreading curves directly from the printed images by fitting them so as to minimize a distance metric between predicted reflectances and measured reflectances at selected relatively uniform locations. We compare the prediction accuracy of the so-calibrated YNSN model with the prediction accu- racy of the same model calibrated by the spectral reflectances of classical uniform calibration patches. Interestingly, when the model is calibrated from image tiles originating from the same or from a similar color image as the one comprising the test tiles, better pre- diction results are obtained than when performing a classical cali- bration on 50% halftone patches printed in all superposition conditions. © 2009 Society for Imaging Science and Technology. DOI: 10.2352/J.ImagingSci.Technol.2009.53.3.030502

Influence of background and surround on image color matching

AbstractIn this article, the corresponding‐color data for complex images reproduced on different media were obtained by simultaneous matching using an adjustment method. In our experiment printed color images and images displayed on a monitor were compared in different viewing conditions. The viewing condition varied in surround relative luminance and background. The experimental data show that surround relative luminance has little influence on color matching between printed and monitor images while changes in background modify color appearance. These results were used to evaluate different chromatic adaptation transforms (CAT). We found that for the same viewing conditions the SHARP transform shows the best agreement between the experimental and predicted data. SHARP transform can not predict accurately corresponding colors for blue and black regions. Therefore, we proposed new CAT that shows better characteristics than other transforms for cyan, green, and black colors and similar characteristics for other colors. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 244–251, 2007