Test Targets 3.1: A Collaborative effort exploring the use of scientific methods for color imaging and process control.

In general, test targets represent known values from an object or in a digital file, e.g., color patches, digital dots, lines with known dimensions, etc. The Macbeth ColorChecker is an analog target with 24 physical color patches. When captured by an input device and reproduced by an imaging system, we can compare tone and color relationships between the source target and its reproduction. On the other hand, the IT8.7/3 target is a digital file consisting of hundreds of patches with known CMYK digital values. When printed along side a signature, we can assess print quality quantitatively with the use of optical instruments and associated analysis techniques. - p. ii

Using Computer Vision to Build a Predictive Model of Fruit Shelf-life

Computer vision is becoming a ubiquitous technology in many industries on account of its speed, accuracy, and long-term cost efficacy. The ability of a computer vision system to quickly and efficiently make quality decisions has made computer vision a popular technology on inspection lines. However, few companies in the agriculture industry use computer vision because of the non-uniformity of sellable produce. The small number of agriculture companies that do utilize computer vision use it to extract features for size sorting or for a binary grading system: if the piece of fruit has a certain color, certain shape, and certain size, then it passes and is sold. If any of the above criteria are not met, then the fruit is discarded. This is a highly wasteful and relatively subjective process. This thesis proposes a process to undergo to use computer vision techniques to extract features of fruit and build a model to predict shelf-life based on the extracted features. Fundamentally, the existing agricultural processes that do use computer vision base their distribution decisions on current produce characteristics. The process proposed in this thesis uses current characteristics to predict future characteristics, which leads to more informed distribution decisions. By modeling future characteristics, the process proposed will allow fruit characterized as “unfit to sell” by existing standards to still be utilized (i.e. if the fruit is too ripe to ship across the country, it can still be sold locally) which decreases food waste and increases profit. The process described also removes the subjectivity present in current fruit grading systems. Further, better informed distribution decisions will save money in storage costs and excess inventory. The proposed process consists of discrete steps to follow. The first step is to choose a fruit of interest to model. Then, the first of two experiments is performed. Sugar content of a large sample of fruit are destructively measured (using a refractometer) to correlate sugar content to a color range. This step is necessary to determine the end-point of data collection because stages of ripeness are fundamentally subjective. The literature is consulted to determine “ripe” sugar content of the fruit and the first experiment is undertaken to correlate a color range that corresponds to the “ripe” sugar content. This feature range serves as the end-point of the second experiment. The second experiment is large-scale data collection of the fruit of interest, with features being recorded every day, until the fruit reaches end-of-life as determined by the first experiment. Then, computer vision is used to perform feature extraction and features are recorded over each sample fruit’s lifetime. The recorded data is then analyzed with regression and other techniques to build a model of the fruit’s shelf-life. The model is finally validated. This thesis uses bananas as a proof of concept of the proposed process

Reproducing wooden and marble patterns using multi-channel ICC profile

Gravure can reproduce a high quality images because of its capacity to lay down ink films of variable thickness, especially for long runs and high color saturation; this aspect provides a very high shadow detail just like photograph. Many organizations have tried to standardize printing like Fogra, ISO, and more. Larger gamut are being built to cover more out-of-gamut colors, but designs, graphics and colorfulness of the products, are limited due to the involvement of several process variables. In publication printing, only four colors of ink are used: yellow, magenta, cyan, and black. CMYK primaries are generally used because the images to be printed have memory colors (blue sky, green grass) or colors that are obtainable within the CMYK gamut. ICC color management helps the user to build ICC profile is to establish which color is produced when a given combination of CMYK dots are printed. However flooring and wooden patterns printing industry, which often uses gravure printing, use non-CMYK primaries because they are better tuned to the limited color space of such patterns. To successfully reproduce these colors, a smaller or customized gamut is selected. Today proprietary software applications are being used for selection and separation of the non-CMYK primaries to obtain the smaller gamut. This research focused on new non proprietary software for selecting primaries and building multi-channel spot color ICC profiles for reproducing the marble and tile patterns

Test Targets 8.0: A Collaborative effort exploring the use of scientific methods for color imaging and process control

Publishing is both a journey and a destination. In the case of Test Targets, the act of creating and editing content, paginating and managing digital assets, represents the journey. The hard copy is the result or destination that readers can see and touch. Like the space exploration program, everyone saw the spacecraft that landed on the moon. It was the rocket booster that made the journey from the earth to the moon possible. This article portrays the process of capturing ideas in the form of digital data. It also describes the process of managing digital assets that produces the Test Targets publication

Quality Analysis of a Printed Natural Reference Image

Tämän diplomityön tarkoituksena oli tutkia paperin vaikutusta koettuun kuvanlaatuun. Päätavoitteeksi asetettiin automaattisen, objektiivisen ohjelmistojärjestelmän kehittäminen ennustamaan ihmisen arviota paperin kuvanlaatuominaisuuksista. Tutkimusprojekti koostui neljästä vaiheesta: testikuvan suunnittelusta kuvanlaadun tutkimukseen, subjektiivisen kokonaislaadun ja laatuattribuuttien arvioinnista testikuvasta, ohjelmiston kehittämisestä ennustamaan laatuattribuutteja sekä visuaalisen laatumallin muodostamisesta ilmaisemaan kokonaislaatua yhdellä laatuarvosanalla. Tutkimuksessa käsiteltiin neljää laatuattribuuttia: värikkyyttä, kontrastia, terävyyttä ja kohinaa. Painatusmenetelmänä käytettiin mustesuihkutulostusta. Ensimmäisessä vaiheessa luotiin luonnollinen referenssikuva kuvanlaadun subjektiivista ja objektiivista arviointia varten. Suunnittelussa painotettiin laatuominaisuuksien lisäksi korkean tason ominaisuuksia, kuten luonnollisuutta, tasapainoa, ja esteettistä vaikutelmaa. Erityispiirteenä kuvaan lisättiin seitsemän GretagMacbeth testiväriä, jotka sisällytettiin kuvassa sijaitseviin luonnollisiin esineisiin. Seuraavassa vaiheessa suoritettiin subjektiivinen testaus ihmisen visuaalisen laatuarvion mittaamiseksi, josta saatuja laatuattribuuttien referenssiarvoja käytettiin objektiivisten laatumittojen suunnittelussa Matlab-ohjelmistolle. Lopuksi kehitetyt laatumitat yhdistettiin tilastollisen regressioanalyysin avulla yhdeksi arvosanaksi paperin kokonaislaadusta, ns. visuaaliseksi laatumalliksi. Myös laatuattribuuteille muodostettiin regressiomallit. Tutkimuksen tuloksena luotiin toimivat ja tilastollisesti tarkat objektiiviset mitat kolmelle laatuattribuutille: värikkyydelle, kontrastille ja kohinalle. Lisäksi kehitettiin mitta värivirheen laskentaan. Myös visuaalisen laatumallin toteutuksessa onnistuttiin hyvin, ja kaikkien regressiomallien selitysasteet olivat tilastollisesti korkeita. Subjektiivisten arvosanojen samankaltaisuus laadun ja laatuattribuuttien välillä johti kuitenkin ongelmiin regressiomallien yleistämisessä, mistä johtuen mallien käyttöä ei voitu suositella reaalimaailman sovelluksissa. Erityistä paneutumista vaativat myös testikuvan suuri värikkyys sekä ohjelmallisten laatumittojen optimointi paperi- ja painatusympäristöön.This thesis was contributed to study the image quality properties of printing papers. The main goal was to produce an automatic, objective software system for predicting human opinion on the print quality of papers. To reach this goal, the project was divided into four phases: the development of a reference image for image quality evaluation, the assessment of subjective print quality from the reference image, the programming of quality analysis software for quality attributes, and the construction of a single grade for print quality, visual quality index (VQI). Four low-level quality attributes were studied: colorfulness, contrast, sharpness, and noise. Only inkjet printing technology was covered. In the first phase, a natural reference image was developed for subjective and objective image quality testing. Focus was placed not only on quality aspects, but also on the high-level properties of the image, i.e. naturalness, balance, and aesthetical expression. Furthermore, presenting a unique feature for a reference image of this kind, seven GretagMacbeth test colors were implemented into natural objects in the image. During later phases, subjective tests were arranged to gather the subjective reference data of print quality for software development with Matlab. Finally, the computed quality attribute scores were combined with statistical regression analysis into a single grade for the print quality of papers, VQI, accompanied with individual regression models for the quality attributes. The outcome of the software development was three functional and statistically accurate Matlab implementations, i.e. for colorfulness, contrast, and noise, complemented with a color difference method. The implementation of the VQI was successful as well, showing remarkably strong goodness measures. However, the generalization of the regression models was compromised by the strong cross-attribute similarity of the subjective reference data, eventually preventing the feasibility of the models in real world applications. Other issues requiring attention included handling the high colorfulness of the reference image and optimizing the software to the print context

Human Jury Assessment of Image Quality as a Measurement: Modeling with Bayes Network

Image quality assessment has been done previously manually by human jury assessment as reference. Due to lack of rationality in human jury voting and its high costs it is desirable to replace it with instrumental measurements that can predict jury assessment reliably. But high uncertainty in jury assessments and sensitivity of image context make it cumbersome for the instrumental measurements. Previous research has shown that modeling with a Bayesian network can resolve some of the problems. A Bayesian network is a belief network of causal model representation of multivariate probabilistic distributions that describes the relationships between the interacting nodes in the form of conditional independency. By conditioning and marginalization operations we can estimate the conditional probabilities of unmeasured elements and their uncertainty in Bayes network. In this thesis we have considered a four-layer pre-existing Bayes network consisting of both qualitative and quantitative component and we have tried to assess probabilities of quality elements assessed by jurors based on instrumental measurement values. To analyze and to quantify the relationship between perceptual quality elements and instrumental measurements, we have calculated mutual information from our provided data set. Based on mutual information calculation and Kullback-Leibler distance measure we have investigated the sensitivity of the network, and we have tried to validate a feasible network model where network parameters have been selected such a way that it minimizes the uncertainties of our chosen Bayes network

Test targets 5.0: A Collaborative effort exploring the use of scientific methods for color imaging and process control

Test Targets is about scholarship that intimately involves faculty and students in the process of writing and publishing. It is a collection if research papers that require collaborative effort over a time span of three academic quarters. Initially, students learned metrology, color management system, and the use of test targets for device optimization and process control. As time goes by, students are encouraged to identify research topics, formulate methodologies, and carry out experiments and data analyses in order to have specific findings. - p.

Appearance-based image splitting for HDR display systems

High dynamic range displays that incorporate two optically-coupled image planes have recently been developed. This dual image plane design requires that a given HDR input image be split into two complementary standard dynamic range components that drive the coupled systems, therefore there existing image splitting issue. In this research, two types of HDR display systems (hardcopy and softcopy HDR display) are constructed to facilitate the study of HDR image splitting algorithm for building HDR displays. A new HDR image splitting algorithm which incorporates iCAM06 image appearance model is proposed, seeking to create displayed HDR images that can provide better image quality. The new algorithm has potential to improve image details perception, colorfulness and better gamut utilization. Finally, the performance of the new iCAM06-based HDR image splitting algorithm is evaluated and compared with widely spread luminance square root algorithm through psychophysical studies

Perceptual Fidelity for Digital Color Imagery

The problem of measuring the fidelity of digital color images in a manner that corresponds to human perceptual assessments is addressed. Experiments are performed to validate human visual system (HVS) models, which provide access to a \u27perceptual space\u27 in which visual distortions may be measured, and then a model is proposed for assessing the perceptual fidelity of digital color image. Color Mach bands are produced in the first experiment, demonstrating that, as in the brightness channel, low spatial frequency attenuation occurs in the chromatic channels of the HVS. In the second experiment, a correlation between the chromatic channels of the HVS model and color discrimination axes of color blind observers is demonstrated. Removing variation from one of the chromatic channels of a natural image produces a color-distorted image which the color blind subjects cannot distinguish from the original. Removing variation from the other chromatic channel produces an image that appears colorful to normally-sighted observers, but monochrome to the color blind observers. The third experiment shows that a Gabor filter-based HVS model produces illusory contours in several illusory contour stimuli. These results provide a unique validation of multiple-channel HVS models which process the image in multiple spatial frequency bands that are tuned to match measured sensitivities of neurons in the primary visual cortex of cats and monkeys. Finally, the multiple-channel processing used in the illusory contour experiment is combined with the color vision model from the first two experiments to produce a multiple-channel, color HVS model for measuring perceptual fidelity of color images. A demonstration of the model shows that the structure of the new model is correct. However, inaccurate parameter values for the multiple-channel processing of the chromatic channels cause over-prediction of visible differences in these channels

Multi-Sensory Interaction for Blind and Visually Impaired People

This book conveyed the visual elements of artwork to the visually impaired through various sensory elements to open a new perspective for appreciating visual artwork. In addition, the technique of expressing a color code by integrating patterns, temperatures, scents, music, and vibrations was explored, and future research topics were presented. A holistic experience using multi-sensory interaction acquired by people with visual impairment was provided to convey the meaning and contents of the work through rich multi-sensory appreciation. A method that allows people with visual impairments to engage in artwork using a variety of senses, including touch, temperature, tactile pattern, and sound, helps them to appreciate artwork at a deeper level than can be achieved with hearing or touch alone. The development of such art appreciation aids for the visually impaired will ultimately improve their cultural enjoyment and strengthen their access to culture and the arts. The development of this new concept aids ultimately expands opportunities for the non-visually impaired as well as the visually impaired to enjoy works of art and breaks down the boundaries between the disabled and the non-disabled in the field of culture and arts through continuous efforts to enhance accessibility. In addition, the developed multi-sensory expression and delivery tool can be used as an educational tool to increase product and artwork accessibility and usability through multi-modal interaction. Training the multi-sensory experiences introduced in this book may lead to more vivid visual imageries or seeing with the mind’s eye