A Study on the Effect of Fabric Structure and Finishing on Perceived Image Quality

Valued at nearly US 7.5 billion, the global textile industry continues on a growth trajectory. Printed textiles represent a major segment of the market, and are making significant contributions to the overall expansion of the industry. Historically, screen printing has dominated the printed textile market, but digital technologies continue to make inroads (Hayward, 2016). One of the problems encountered in the textile industry is obtaining the desired color. Studies have shown that the texture and finishing of a fabric can have an impact on the way the ink sets on the fabric and in turn effect the quality of image. Valentini (2012) concluded in her study that the quality of the image is an important consideration for buyers. However, defining image quality attributes that correlate with the human perception of overall quality can be difficult. Hence, the present study is rooted in the early works of Engeldrum (2004) who stated that image quality depends on the “nesses“ (e.g. colorfulness, lightness, sharpness) rather than on physical image parameters. According to him these “nesses” relate to human perception of quality. Building on Engeldrum’s work, Pederson et al. (2010) formulated a more practical approach by distilling image quality attributes into the five most meaningful (i.e., colorfulness, lightness, contrast, sharpness and artifacts). In addition, Pederson et al. (2010) recommend researchers operationalize overall image quality as a separate construct, recognizing that it encompasses the other five attributes. These have been deployed in the present study. A Likert scale was developed and thirty participants were recruited for a psychophysical experiment. A test form was printed on four fabrics of different texture and sheen combination and the participants were asked to rate these fabrics based on the six image quality attributes. The data obtained was statistically analyzed and the results indicate that a Low Texture and Low Sheen fabric was preferred the most and Image Sharpness is the most effective image attribute for consumers. The study also led to the conclusion that image quality is subjective and observer dependent and also implies that the structural properties of fabrics or substrates can have an impact on the perceived image quality

An Analysis of the factors influencing paper selection for books of reproduced fine art

Toner-based digital presses are now capable of matching offset lithographic presses in image and print quality. Current trends show increased interest in printing fine art books on digital presses. It is necessary to understand the extent to which digital printing systems are capable of accurately rendering fine-art reproductions. This research analyzed paper properties that maximize image quality and preference for digitally printed fine art reproductions. Four images, representing four art media, were printed on twelve papers using two digital presses. The twelve papers represented different combinations of color, print-show-through, roughness and gloss. A psychophysical experiment was conducted in which observers ranked the twelve papers for each image on the basis of image quality, color rendering quality, and surface appearance quality. The results were analyzed and a model was developed to predict the probability that a paper was ranked in the top three. Paper color (coolness), basis weight, roughness, and gloss were model parameters. Unlike gloss, roughness, and print-show-through, there was no previous metric for quantifying coolness. Therefore, an additional experiment was conducted to develop a model to predict the perception of coolness using colorimetry. An alternative experiment model was also developed that included parameters such as caliper, print gloss, line raggedness, and dot circularity. The resulting models allowed for the optimization of paper parameters that maximize the probability a paper will produce preferred and high quality images. It was concluded that the probability a book was judged as having high image quality was optimized for papers with high coolness, low roughness and low gloss. Neither print show-through, line raggedness, nor mottle were significant factors. An additional lexical analysis was performed for observer descriptions of their ranking behavior. This analysis provided complementary data to the psychophysical results. Observers\u27 descriptions of their ranking strategies did not match the rank data, suggesting a possible disconnect between observers\u27 conscious and subconscious ranking behaviors

An Analysis of the factors influencing paper selection for books of reproduced fine art printed on digital presses

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Consumer perception of inkjet printed textiles

Digital inkjet printing for textile printing represents a key development in clothing production. The application of inkjet printing for textiles follows the trends within both the printing and textile industries in regards to the demand for personalization in order to gain consumer interest and buying power. There has been much research done in the hopes of getting inkjet printed textiles to the public on a mass scale. However, very little is known regarding the consumer on their preferences when it comes to the image quality, look, and feel of digitally printed textiles. This study attempted to address this problem by finding out such preferences from not just the consumer but also the buyer of merchandise, specifically that of the boutique market, for clothing stores. There were two methods utilized within this experiment. The first is the use of structured interviews of boutique owners within the high end boutiques of Rochester, NY to find out what their general feelings on fashion, clothing and print on demand textile options are. The boutique owners were interviewed for approximately 30 minutes through the use of a formatted structured interview. The second part of this experiment was a psychophysical experiment. This part of the experiment dealt with the image quality preferences of the boutique owners and observers, that fell within a specific set of criteria outlined by the researcher, for inkjet printed textile samples. The observers were asked to rank order the different inkjet samples according to preference of image quality, tactile feel and for specific applications. This part of the experiment took approximately 30 minutes for the observer to complete and followed an experiment outline. It is through the qualitative and quantitative data gathered by both parts of the experiment that the researcher has attempted to answer the research objective, what does the consumer prefer in regards to image quality and feel of inkjet printed textiles? The findings of the experiment show that the consumer is highly aware of the image quality within their clothing and specifically favor textiles with high OBAs and tighter weaves of fiber. Depending on the application of a shirt or a bag the observer showed that tactile feeling is more important to the observer for clothing but image quality standards are willing to be lowered when dealing with accessories such as the bag as long as the sturdiness of the textile is acceptable

Subjective Image Quality Assessment of Digitally Printed Images

Smartphones have become ingrained in our daily activities, driving their cameras to become better with every generation. As more and more images are being taken by cell phones it has become increasingly important to assess the quality of the images taken by different phones. While many cell phone images are only viewed electronically, many images also get transformed into printed images, especially photo-books, as digital printing gets better and cheaper compared to traditional printing processes. The gap between electronic image and printed image in shrinking rapidly and it becomes important to study the transition of images from screen to paper. The main goal of this research was to perform a rank order experiment for assessing cell phone image capture quality that translates to printed images via several different digital printers. It was of interest to investigate whether the overall image quality on displays correlates well with printed image quality. The important aspect was to study was to observe if there is a loss of image quality due to different digital printers

Investigation into the perceived image quality of digital technologies for photofinishing

With the shift from silver halide film to pixels, the possibilities for photofinishing have burgeoned as well. Not much more than a decade ago, photography was a process involving the recording of images on film and the printing of these images on silver halide paper. Today the majority of images are now captured digitally, and though digital silver halide certainly remains an important player in the photofinishing market, a great many images are printed at home on ink jet printers. Images are also being printed in forms other than 4 x 6 in. prints. Electrophotographic printing technology is being used to generate photo books, cards, and calendars. In addition, wide-format ink jet and, eventually, high-speed ink jet, afford still other opportunities. It is of interest, then, to understand the perceptual image quality being achieved using the various printing technologies today. The objective of this project is to evaluate the perceived image quality of ink jet and electrophotographic photo finishing relative to digital silver halide. Targets generated to resemble photo album pages, along with a variety of photo books, were used in this study. The observers for this project were selected to represent typical consumers rather than individuals who are more skilled in image evaluation. The results indicate that: the observers generally found higher value in the full-size photo books and ink jet prints relative to the electrophotographic prints and the Pocket Portfolio mini photo book; that first-person images did not rank substantially differently from third-person images—at least for images that did not contain humans; and that the photo print format had a more significant impact on the assigned value than the image content

A Black-Point Adaption model for color reproduction

Based on the current state of CIECAM97s, there is a missing adjustment associated with a black-point unlike a white-point. As an attempt to improve the performance of CIECAM97s for color reproduction, six algorithms focusing on black-point adaptation were generated based on previous work on white-point adaptation methods and gamut mapping methods. The six algorithms were used to reproduce four original images targeted to four simulated hard-copy viewing environments that were only differentiated by their black-point settings. Then, the six algorithms were tested in a psychophysical experiment with 32 observers. As a result, linear lightness rescaling under the luminances of white and black of a specific setting was demonstrated to be the best color reproduction method across different black-point settings. The adapted black-point was defined as having the lowest lightness value with its default chromatic appearance correlates predicted by the current state of CIECAM97s under the input viewing environment and was reproduced accordingly with the same appearance correlates

The LLAB model for quantifying colour appearance

A reliable colour appearance model is desired by industry to achieve high colour fidelity between images produced using a range of different imaging devices. The aim of this study was to derive a reliable colour appearance model capable of predicting the change of perceived attributes of colour appearance under a wide range of media/viewing conditions. The research was divided into three parts: characterising imaging devices, conducting a psychophysical experiment, and developing a colour appearance model. Various imaging devices were characterised including a graphic art scanner, a Cromalin proofing system, an IRIS ink jet printer, and a Barco Calibrator. For the former three devices, each colour is described by four primaries: cyan (C), magenta (M), yellow (Y), and black (K). Three set of characterisation samples (120 and 31 black printer, and cube data sets) were produced and measured for deriving and testing the printing characterisation models. Four black printer algorithms (BPA), were derived. Each included both forward and reverse processes. A 2nd BPA printing model taking into account additivity failure, grey component replacement (GCR) algorithm gave the most accurate prediction to the characterisation data set than the other BPA models. The PLCC (Piecewise Linear interpolation assuming Constant Chromaticity coordinates) monitor model was also implemented to characterise the Barco monitor. The psychophysical experiment was conducted to compare Cromalin hardcopy images viewed in a viewing cabinet and softcopy images presented on a monitor under a wide range of illuminants (white points) including: D93, D65, D50 and A. Two scaling methods: category judgement and paired comparison, were employed by viewing a pair of images. Three classes of colour models were evaluated: uniform colour spaces, colour appearance models and chromatic adaptation transforms. Six images were selected and processed via each colour model. The results indicated that the BFD chromatic transform gave the most accurate predictions of the visual results. Finally, a colour appearance model, LLAB, was developed. It is a combination of the BFD chromatic transform and a modified version of CIELAB uniform colour space to fit the LUTCRI Colour Appearance Data previously accumulated. The form of the LLAB model is much simpler and its performance is more precise to fit experimental data than those of the other models

N-colour separation methods for accurate reproduction of spot colours

In packaging, spot colours are used to print key information like brand logos and elements for which the colour accuracy is critical. The present study investigates methods to aid the accurate reproduction of these spot colours with the n-colour printing process. Typical n-colour printing systems consist of supplementary inks in addition to the usual CMYK inks. Adding these inks to the traditional CMYK set increases the attainable colour gamut, but the added complexity creates several challenges in generating suitable colour separations for rendering colour images. In this project, the n-colour separation is achieved by the use of additional sectors for intermediate inks. Each sector contains four inks with the achromatic ink (black) common to all sectors. This allows the extension of the principles of the CMYK printing process to these additional sectors. The methods developed in this study can be generalised to any number of inks. The project explores various aspects of the n-colour printing process including the forward characterisation methods, gamut prediction of the n-colour process and the inverse characterisation to calculate the n-colour separation for target spot colours. The scope of the study covers different printing technologies including lithographic offset, flexographic, thermal sublimation and inkjet printing. A new method is proposed to characterise the printing devices. This method, the spot colour overprint (SCOP) model, was evaluated for the n-colour printing process with different printing technologies. In addition, a set of real-world spot colours were converted to n-colour separations and printed with the 7-colour printing process to evaluate against the original spot colours. The results show that the proposed methods can be effectively used to replace the spot coloured inks with the n-colour printing process. This can save significant material, time and costs in the packaging industry

Evaluating Appearance Differences of Color 3D Printed Objects

Color 3D printing is a relatively young technology with several exciting applications and challenges yet to be explored. One of those challenges is the effect that three dimensional surface geometries have on appearance. The appearance of 3D objects is complex and can be affected by the interaction between several visual appearance parameters such as color, gloss and surface texture. Since traditional printing is only 2D, several of these challenges have either been solved or never needed to be addressed. Complicating matters further, different color 3D printing technologies and materials come with their own inherent material appearance properties, necessitating the study of these appearance parameters on an individual case by case basis. Neural networks are powerful tools that are finding their way into just about every field imaginable, and the world of color science is no exception. A process described by previous researchers provides a method for picking out color sensitive neurons in a given layer of a convolutional neural network (CNN). Typically, CNNs are used for image classification but can also be used for image comparison. A siamese CNN was built and shown to be a good model for appearance differences using textured color patches designed to simulate the appearance of color 3D printed objects. A direct scaling psychophysical experiment was done to create an interval scale of perceptual appearance between color 3D printed objects printed at different angles. The objects used for this experiment were printed with an HP® Jet Fusion 580 color 3D printer. The objects exhibit print angle dependent surface textures inherent to the layered printing process itself. The preliminary siamese CNN showed that perceptual differences in the prints were likely to exist and could be modeled using a neural network. However, the results of the psychophysical experiment indicated that CIELAB color differences were extremely strong predictors of observer perceptions, even with variable surface texture in uncontrolled lighting conditions