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Precise assessment of harvest yield is a difficult field of work. The equipment and programming stage to foresee the harvest yield relies on different components like climate, soil fruitfulness, genotype, and different collaborating wards. The assignment is unpredictable inferable from the information that should be gathered in volumes to comprehend crop yield through remote sensor organizations and distant detecting. This paper audits the previous 15 years of exploration work in the improvement of assessing crop yield utilizing profound learning calculations. The meaning of examining progressions utilizing profound learning methods will help in dynamic for foreseeing the harvest yield. The cross breed mix of profound learning with distant detecting and remote sensor organizations can give accuracy agribusiness later on.

Depending on the different types of raw materials used to produce hanji, a Korean traditional handmade paper, there can be significant differences in the durability and mechanical properties of the final product. In this study, near-infrared spectroscopy (NIR) combined with multivariate statistical methods were used to confirm the classification possibility of hanji based on the various type of raw materials. The hanji papers were prepared from paper mulberry trees, cooking agents, and mucilage. Altogether, a total of 60 hanji spectra were collected by NIR. Then, the 60 spectra were grouped into four categories: the control, paper mulberry, cooking agent, and mucilage type based on each of the types of raw materials contained in the hanji. Three different classification algorithms – partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and random forest (RF) – were used to classify the hanji types. The best hanji material classification performance was obtained when the hanji samples were classified according to paper mulberry type, wherein the prediction accuracies of PLS-DA, SVM, and RF were 100%, 100%, and 98%, respectively. These results suggested that NIR in combination with multivariate statistical methods can be used for hanji material classification.

International audience; We report a pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) method capable of analyzing traditional East Asian papers. The method proposed is based on rapid and easy single step Py-GC/MS analysis that can be carried out with a minimum amount of matter, in the few g range. Three reference papers manufactured from kozo (Broussonetia kazinoki Siebold & Zucc.), mitsumata (Edgeworthia chrysantha Lindl.) and gampi (Wikstroemia sikokiana Franch. & Sav.) with the traditional hand paper making processes were examined. The method allows discrimination between terpenic and steroid compounds, which were revealed as chemical markers of origin of the plant fibers. Each paper investigated was found to have characteristic pyrolysis fingerprints that were unique to the traditional handmade paper, demonstrating the potential for differentiation of these biochemical components of fiber plants on East Asian papers towards identification and conservation of cultural heritage. The investigation on Py-GC/MS was extended to liquid extraction followed by GC/MS analysis to characterize the biochemical components of fiber plants. The main contribution of this study is to provide molecular criteria for discriminating plant species used for traditional East Asian hand papermaking. Py-GC/MS complements efficiently microscope identification especially for adverse cases. A case study of archaeological Chinese paper painting artefacts was thereafter successfully investigated to address informative potential and efficiency of the criteria of identification on ancient and degraded East Asian paperworks.

Diffuse reflectance ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy is applied as a means of differentiating various types of writing, office, and photocopy papers (collected from stationery shops in India) on the basis of reflectance and absorbance spectra that otherwise seem to be almost alike in different illumination conditions. In order to minimize bias, spectra from both sides of paper were obtained. In addition, three spectra from three different locations (from one side) were recorded covering the upper, middle, and bottom portions of the paper sample, and the mean average reflectivity of both the sides was calculated. A significant difference was observed in mean average reflectivity of Side A and Side B of the paper using Student's pair t-test. Three different approaches were used for discrimination: (1) qualitative features of the whole set of samples, (2) principal component analysis, and (3) a combination of both approaches. On the basis of the first approach, i.e., qualitative features, 96.49% discriminating power (DP) was observed, which shows highly significant results with the UV-Vis-NIR technique. In the second approach the discriminating power is further enhanced by incorporating the principal component analysis (PCA) statistical method, where this method describes each UV-Vis spectrum in a group through numerical loading values connected to the first few principal components. All components described 100% variance of the samples, but only the first three PCs are good enough to explain the variance (PC1 = 51.64%, PC2 = 47.52%, and PC3 = 0.54%) of the samples; i.e., the first three PCs described 99.70% of the data, whereas in the third approach, the four samples, C, G, K, and N, out of a total 19 samples, which were not differentiated using qualitative features (approach no. 1), were therefore subjected to PCA. The first two PCs described 99.37% of the spectral features. The discrimination was achieved by using a loading plot between PC1 and PC2. It is therefore concluded that maximum discrimination of writing, office, and photocopy paper could be achieved on the basis of the second approach. Hence, the present inexpensive analytical method can be appropriate for application to routine questioned document examination work in forensic laboratories because it provides nondestructive, quantitative, reliable, and repeatable results.

Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. © 2019 Howison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

International audience; An analytical approach based on the multivariate analysis of on-line pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) data is proposed for the identification of traditional East Asian handmade papers from different fiber material origins. This approach utilized several biomarkers detected during Py-GC/MS analysis of the paper samples. At first, the total ion chromatogram (TIC) was taken as the response and then the extracted ion chromatograms (EICs) were considered to improve the discrimination of papers. The influence of different data pretreatment (raw responses vs normalized values) including different weighting of the variables (weighting as 1 vs weight as 1/STD, where STD stands for standard deviation) for principal component analysis was also investigated. The results showed that compared to the commonly used microscopy techniques, the Py-GC/MS technique proved to be able to discriminate against handmade paper materials that have similar microscopic morphologies such as Morus species vs. Broussonetia species. The data pretreatment influenced the PCA modeling: the analysis based on normalized values showed more interpretable PCA group features for Moraceae species. PCA without weighting resulted unsurprisingly in discrimination through the presence of high intensity response biomarkers, while when applying weight as 1/STD, PCA loading plot was shown to provide a group of compounds, most of them being present at low levels, to be discriminating. Additionally, the characteristic EICs can provide data matrix for statistical analysis avoiding the interference from co-eluting compound and background compared to the data matrix obtained from the TIC. As a result, a quick Py-GC/MS based handmade paper identification procedure using PCA modeling of characteristic EICs was for the first time proposed in the identification of traditional East Asian handmade papers. This procedure could be very beneficial in cultural heritage applications.

The dating of documents is one of the pending issues to be resolved in many fields. Although there are a variety of analytical methodologies focused on the inks of documents to estimate the dating of documents, the analysis of documents itself attracted little attention. A non-destructive method based on Fourier transformed infrared (FTIR) was proposed in this research to estimate the dating of documents. First, FTIR spectra of journals dated from 1940 to 1980, naturally aged and conserved in the China Agriculture University library were collected. Second, the least squares support vector machines (LS-SVM) was applied to distinguish documents of different dating, and the accuracy was 99.26%. In order to find interested wavenumber that influence the dating process of documents, sparse partial least squares (sPLS) was applied to select informative variables. The average of selected variables was 483 after 100 runs, and the selected variables were focused on the absorption peaks of inorganic components and cellulose. Splicing sPLS with LS-SVM (sPLS–LS-SVM) built model to see the effective of selected variables. Average accuracy of sPLS–LS-SVM model was 99.34%, even the best result could reach 100.00% after 100 circle times. The present work indicates that the possibility of FTIR combined with chemometrics can estimate the dating of documents accurately. Additionally, the wavenumber which influence the dating of documents are mostly focused on cellulose and inorganic components.

Different types of paper and different basis weight of the same paper are selected in order to study the relationship between paper and color reproduction. Comparing with the reference data set, the influence of paper on color reproduction is analyzed from the color difference and color gamut. The results show that the colorimetric value of paper is more closer to the reference data set, the average color difference of patches is more smaller. The color reproduction ability of offset paper is weaker than that of other paper in the experiment. The color reproduction ability of different basis weight of the same paper is also slightly different. Therefore, the type and basis weight of the paper affect the color reproduction. In the process of printing proofs, it is considered that paper has a certain impact on color reproduction.

Paper is non-uniform; thus, it is difficult to ascertain whether the slight differences in near-infrared absorption spectra are caused by the difference in paper type or the paper’s non-uniformity. We used near-infrared hyperspectral imaging to measure the spectra of many different points quickly for eight different paper samples. Next, we analysed the data using machine learning and constructed a model to ascertain whether the differences in the spectra are due to the difference in paper type or the paper’s non-uniformity. Even papers with very similar spectral shapes were distinguished with high accuracy with this method. As the number of spectra used to construct the classification model increased, the accuracy of the classification model increased. With 6840 spectra per sample, the accuracy exceeded 85%, and with 68,400 spectra per sample, the accuracy for identification was 87.8%.

Studying of paper carriers of information has become increasingly important in forensic practice. This is caused by growing number of bogus or in other manner fraudulently alternated documents. An identification of individual paper sheets and studying their differences are the parts of forensic analysis of multiple sheets documents. This paper focuses on the possibilities of processing of mathematical and statistical data obtained by measurements of FT-IR spectral characteristics of individual paper sheets in a studied document. The spectral data were used to create data matrix which contains values of absorbance and interval of wavenumber. The method of differentiation is based on the comparison of maximum absorbance values within the range of wavenumbers from 1562 to 1215 cm−1. This spectrum range is specific in occurrence of absorption bands that belong to calcium carbonate CaCO3—an element of paper added into it in relatively high amounts in the form of filler which content or percentage occurrence may be different considering to the paper producer or production technology. Based on the above-said, the paper sheets originating from different producers or from various production technology units can be differentiated one from another using a robust statistical analysis.

In this paper a new method is proposed for intelligent sort of battery from waste paper based on Invariant Moments and Fractal Dimension (IMFD). In IMFD, a new distinctive feature that based on the edge contours is extracted to describe the target picture. At first invariant moments technique is used to extract Hus seven moments as the global descriptors from the target image. Then the fractal dimensions are extracted as local invariant descriptors by using Fractal Dimension. At last, a combing descriptor is built according the distinctive feature, which combines the global descriptor and the local descriptor together. The features are highly distinctive, and can be matched with high probability against a large database of features. The practical tests performed in this article show that the proposed method has a significant effect on increasing the stability, the accuracy of classification, and also can effectively against the huge-information during the image processing.

This study investigated the effects of bending curvature of simulated e-paper displays (−10 cm, plane and 10 cm) and ambient illuminance (50, 500, 6000 and 12,000 lx) on the visual performance of young and elderly users for simulated electronic-paper displays. In total, 24 people comprising 12 young and 12 elderly users participated in this study. Young users demonstrated significantly enhanced visual performance using the simulated electrophoretic ink (E ink) e-paper display with ambient illuminance set at 50 and 500 lx; however, participants did not demonstrate significantly different visual performance using the 2 simulated e-paper displays with ambient illuminance set at 6000 and 12,000 lx. The bending curvature did not exhibit significant effects on the visual performance of young participants under various ambient illuminances. The elderly participants exhibited significantly enhanced visual performance using the simulated E ink e-paper display only when ambient illuminance was set at 50 lx; however, participants did not exhibit significantly different visual performance using the two simulated e-paper displays with ambient illuminance set at other levels. Elderly users exhibited significantly enhanced visual performance when the bending curvature was set at 10 cm, with ambient illuminance set at 50 lx. Elderly users also demonstrated significantly enhanced visual performance under bending curvature settings of 10 cm and plane, with ambient illuminance set at 500 lx. However, the bending curvature of the simulated e-paper did not exhibit significant effects on the visual performance of elderly participants under ambient illuminance settings of 6000 and 12,000 lx.

Multi-sensor object detection and tracking on a highway scene with radar measurements is presented. The estimation algorithm is the random finite set based Bernoulli filter, working in the Bayesian framework. The recursion for calculating the Bayes estimation is implemented as a particle filter. A method is presented for calculating the likelihoods, suitable for particle filtering performed with moving sensors, assuming additive Gaussian measurement noise. In our approach, for calculating the posterior estimate of the object state, the measurement likelihoods are computed in the state space, instead of the measurement space, by mapping each measurement to the global coordinate system. The map consists of a nonlinear and an affine part. While the affine transformation trivially preserves the Gaussian nature, the nonlinear is well-proven to be approximated as affine too. This approach allows the particles to be drawn directly from the state space, hence the evaluation of the measurement model is not needed, which saves computational power.

Although flexible neural networks FNNs have been used more successfully than classical neural networks CNNs in many industrial applications, nothing is rigorously known about their properties. In fact they are not even well known to the systems and control community. In the first part of this paper, existing structures of and results on FNNs are surveyed. In the second part FNNs are examined in a theoretical framework. As a result, theoretical evidence is given for the superiority of FNNs over CNNs and further properties of the former are developed. More precisely, several fundamental properties of feedforward and recurrent FNNs are established. This includes the universal approximation capability, minimality, controllability, observability, and identifiability. In the broad sense, the results of this paper help that general use of FNNs in systems and control theory and applications be based on firm theoretical foundations. Theoretical analysis and synthesis of FNN-based systems thus become possible. The paper is concluded by a collection of topics for future work.

Effects of character size under ambient illuminances and light sources on legibility of electronic paper displays (electrophoretic display and cholesteric liquid crystal display) were studied and compared with paper. Sixty subjects participated in a letter-search task in the experiment. The results showed that search speed depends on the illuminance but not light source. Search speed increased as the illuminance increase from 300, 700 to 1500 lx. Search speed also increased with the increase of character size, from character height of 1.4 mm (9.6 min visual angle), 2.2 mm (15.1 min visual angle) to 3.3 mm (22.7 min visual angle), and the increase leveled off at 4.3 mm (29.6 min visual angle). The effect of character size on accuracy was also significant. Accuracy increased with the increase of character size. However, the effect of illuminance and light source on accuracy was not statistically significant. Based on the results of this study, it seems that E-paper displays may need greater illumination (700 lx or higher), greater character size (3.3 mm or 22 min of visual angle).

International audience; This paper investigates the classification of photographic paper tex-tures using visual descriptors. Such classification is called fine grain due to the very low inter-class variability. We propose a novel image representation for photographic paper texture categorization, relying on the incorporation of a powerful local descriptor into an efficient higher-order model deviation where texture is represented by com-puting statistics on the occurrences of specific local visual patterns. We perform an evaluation on two different challenging datasets of photographic paper textures and show such advanced methods in-deed outperforms existing descriptors.

Perfumes are cosmetic products with high added value and worldwide consumption, which make them a potential target for counterfeiting. A novel, simple and rapid method was developed for the differentiation of samples of authentic and counterfeit perfumes by employing paper spray mass spectrometry (PS-MS) combined with multivariate supervised classification models: Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogies (SIMCA). Samples of authentic (n = 29, consisting of 10 different brands from several batches and from the same producer) and seized counterfeit (n = 31) perfumes were analysed by PS-MS in the positive ionization mode and within a mass range of m/z 150–1000. An initial unsupervised exploratory model (Principal Component Analysis – PCA) provided a rough visual separation between the two classes. In contrast, PLS-DA and SIMCA provided good predictions, with low false positive and false negative rates for both models. The interpretation of informative vectors, i.e. regression coefficients and Variable Importance in Projection (VIP) scores obtained from the PLS-DA model allowed the detection of diagnostic ions for authentic and counterfeit samples. Some of the most discriminant ions for counterfeit perfumes were suggested to be attributed to compounds with allergenic properties.

This discussion provides our reaction to the article by Greven and Scheipl. It contains an overview of their article and a description of the many areas of research that remain open and could benefit from further methodological and computational development.

In the last 30 years, several distinguished researchers have proposed and discussed different fuzzy versions of well-known Saaty's Analytic Hierarchy Process (AHP). The paper recently published by K. Zhü in the European Journal of Operational Research heavily criticizes the fuzzy approaches to AHP, claiming the fallacy of all of them. Therefore, it seems to be necessary to clarify whether the criticisms are well-founded or not. The present paper aims to rebut Zhü's claims by showing that the evidences and the reasonings in his paper are very poor and far from proving the fallacy of fuzzy AHP.

In this paper, we achieved the floating 3D image based on integral photography theory to display the image in an oblique viewing angle on portable device. Considering the repeated image overlapping problem in the integral image system, it can be solved by adjusting the receiving angle. In the future, the floating 3D image could integrate with the 3D interactive system to provide more realistic visual experience.

The purpose of this study is to develop a descriptive paper test item which can evaluate elementary school students’ HGA (scientific Hypothesis Generating Ability) and to propose a counting formula that can easily assess student’s HGA objectively and quantitatively. To make the test item can possibly evaluate all the students from 6th graders to 3rd graders, the ‘rabbit’s ear’ item is developed. Developed test item was distributed to four different elementary schools in Seoul. Total 280 students who were in the 6th grade solved the item. All the students’ reponses to the item were analyzed. Based on the analyzed data evaluation factors and evaluation criteria are extracted to design a Hypothesis Generating ability Quotient (HGQ). As the result ‘Explican’s Degree of Likeness’ and ‘Hypothesis’ Degree of Explanation’ are chosen as evaluation factors. Also precedent evaluation criteria were renewed. At first, Explican’s Degree of Likeness evaluation criterion was turned four levels into three levels and each content of evaluation criterion is also modified. Secondly, new evaluation factor ‘Hypothesis’ Degree of Explanation’ was developed as combined three different evaluation criteria, ‘level of explican’, ‘number of explican’ and ‘structure of explican’. This evaluation factor was designed to assess how the suggested hypothesis can elaborately explain the cause of one phenomenon. Newly designed evaluation factors and evaluation criteria can assess HGA more in detail and reduce the scoring discordant through the markers. Lastly, Developed counting formula is much more simple than precedent Kwon’s equation for evaluating the Hypothesis Explanation Quotient. So it could help easily distinguish one student’s scientific hypothesis generating ability.Key words : scientific hypothesis generating ability, evaluation factor, evaluation criteria, hypothesis generating ability quotient, counting formula

Multi-projection three-dimensional (3D) display system with dual projection using uniaxial crystal is proposed. The dual projection means that multiple images are generated by double refraction in the uniaxial crystal according to the polarization state of a single projection unit. The concept of dual projection method is equivalent to physically separated two projectors. We apply the dual projection method in the multi-projection 3D display and double the number of viewing zones while maintaining the number of projectors. Through the experiment, we implement the four-view multi-projection 3D display providing super multi-view condition with two projection units. Experimental results verify the feasibility of the proposed system.

This position paper presents the main problems in classical and modern Fuzzy Theory and gives solutions in Formal Concept Analysis for many of these problems. To support the successful cooperation between scientists from the communities of Fuzzy Theory and Formal Concept Analysis the author starts with this position paper an initiative, called "Pragmatics in Fuzzy Theory".

This paper proposed an improved method based on adaptive with threshold wavelet transform denoising, according to image is often affected by noise pollution in the process of acquisition and transmission, compared with the advantages and disadvantages of traditional digital filtering method. It extracts the structure information and details of the image. It can adaptively select wavelet transform of optimal decomposition level and soft threshold to achieve the optimal noise reduction effect. The Simulation results demonstrate that this theory can effectively filter Gaussian noise and Salt and pepper noise, at the same time well protect the image details and achieve better visual effects.

In order to consummate the management of bank paper, a new algorithm which can recognize the areas of paper tape in bundle of paper money is presented. Image segmentation is used to divide the image into several sub-blocks. Specifically, image entropy is computed in each sub-block. Experimental in different algorithms, including color training algorithm and the median filter and edge detection algorithm, demonstrates its real-time, effectiveness and robustness.

In the present work, the analytical potential of laser induced breakdown spectroscopy (LIBS) for the discrimination of paper types and prints made by digital printers on these papers was assessed. Six different paper types (including standard office papers, color paper and non-bleached paper), and eight printers (including laser and inkjet, as well as color and black printers) were included in the study. Only one or two laser shots were delivered to each sample in order to cause minimal sample destruction and provide maximum spatial resolution. The statistical evaluation of LIBS spectra was performed by multiple methods including three comparative functions (linear correlation, sum of squared deviations and overlapping integral) as well as two advanced statistical methods (multivariate curve resolution alternating least squares (MCR-ALS) combined with classification tree and discriminant analysis (DA)). The best classification results were obtained with the newly introduced MCR-ALS/DA approach, which proved to be 96.3% accurate in the identification of the paper type and 83.3% accurate in the identification of the printer type, based on the LIBS spectrum collected from just a single laser shot to the sample. It was found that the UV part of the LIBS spectrum can be used most efficiently for the discrimination.

This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adaptively coordinated by means of a control parameter that measures fitness distribution among individuals of the population and a novel probabilistic scheme. Numerical results confirm that Differential Evolution is an efficient evolutionary framework for the image processing problem under investigation and show that the EMDE performs well. As a matter of fact, the application of the EMDE leads to a design of an efficiently tailored filter. A comparison with various popular metaheuristics proves the effectiveness of the EMDE in terms of convergence speed, stagnation prevention, and capability in detecting solutions having high performance.

There exist low recognition speed and non-ideal recognition effect in some recognition algorithms of paper currency value. One of very important reasons is that the shooting angle makes the image inclined. This paper firstly analyses the binarization processing of RMB 100-Yuan image and then the method of acquiring straight lines in image is discussed. Thus, the inclination angle of image is calculated by using the obtained straight lines. Finally, through rotation transformation, the inclination image is corrected. The experimental results show that this algorithm has a good corrected effect to the inclination image of paper currency and improves the image recognition effect.

Fiducial markers are used in image processing to determine locations of interest based on fixed points of reference. There are a number of applications for these markers across various fields ranging from advertising to radiation therapy. The four-square fiducial markers discussed in this manuscript allow for the determination of locations of interest on digital images. These new markers are easily detected, provide information about image orientation, and allow for local color sampling. The markers are intended for use in a pharmaceutical assessment process in which images of colorimetric chemical tests are taken by a smart-phone in the field, uploaded to a database, and analyzed to collect quantitative information about the colors resulting from the tests. KEYWORDS: Image Processing; Digital Imaging; Fiducial Markers; Image Thresholding; Color Calibration; MATLAB; Paper Analytical Devices

Selection of the most significant variables, i.e. the wavenumber, from an infrared (IR) spectrum is always difficult to be achieved. In this preliminary paper, the feasibility of genetic algorithms (GA) in identifying most informative wavenumbers from 150 IR spectra of papers was investigated. The list of selected wavenumbers was then employed in Linear Discriminant Analysis (LDA). GA procedure was repeated 30 times to get different lists of variables. Then the performances of LDA models were estimated via leave-one-out cross-validation. A total of six to eight wavenumbers were identified to be valuable variables in the GA procedures. All the 30 LDA models achieve correct classification rates between 97.3% to 100.0%. Therefore the GA-LDA model could be a suitable tool for differentiating white papers that appeared to be highly similar in their IR fingerprints.

Paper properties, including the chemical or optical characteristics influence the quality and colorimetric characteristics of final printed colors. In this study, the effect of gloss, texture, and whiteness of the paper on the printed colors were investigated. The study was applied on 10 coated papers with different texture, gloss or whiteness, and the same grammage using two inkjet printers. It was found that the reproducibility of the printer can be affected with the paper brand, and this effect is statistically dependent on the brand of printer. The kind of paper significantly influences the light fastness of the final printed colors, and this effect statistically depends on the printer. Although, the paper's properties such as gloss and whiteness affect the gamut volume, it is not totally possible to model this effect. The effect of paper on the colorimetric values of the final printed colors is statistically significant. However, the influence of the brand of printer on the color changes via the paper difference is not statistically provable. Edge frequency technique was introduced as an appropriate method for computing texture properties of papers. The texture difference computed by this method shows a suitable correlation with the color differences caused by changing the paper's texture; however, it depends on the printer's brand. Furthermore, there is a good correlation between the Edge frequency difference and the gamut volume variation for papers with different texture while the other parameters such as gloss and whiteness are the same. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 284–291, 2013

Paper, as an important substrate of printed matter, the performance will impact on the color reproduction. Brightness, as a key index of paper performance, affects the apparent color of paper directly. It was investigated that the printed samples with different brightness have been evaluated the influence of paper brightness on color reproduction by the methods of subjective and objective color difference evaluation. Three kinds of paper with different brightness have been selected as substrate of printed samples. The standard test color blocks have been printed to do corresponding objective color difference evaluation to different paper by CIEDE2000 color-difference formulae methods. Meanwhile, the standard test images with difference contents have been printed on three kinds of paper, which was subjected to subjective color difference evaluation for visual evaluation of standard test images in standard observe conditions. The results of subjective and objective color difference evaluation have been combined to analyze the effect of paper brightness to color reproduction, and different visual influence to images of difference content, and could provide certain reference for selecting the brightness performance of paper in color reproduction.

In many sports games, we would use a coin or the game of scissors-paper-stone to decide which side will begin first. We consider the game of scissors-paper-stone when two teams are composed of N respectively. We continue the game of scissors-paper-stone until the winner of the two team is decided. Using sample spaces and enumerating the elements we calculated the mean number of the game when N = 1, N = 2 and N = 3. In case of N = 1 and N = 2, we simulate the game and find the mean and variance when the repetition number n = 20; 30; 50; 100; 150; 200.

A thermal aging experiment was conducted for oil-paper insulation to evaluate the insulation's response under thermal stress. Oil-papers at different aging stages were used to create oil-paper bound gas cavity specimens, which were used to collect data on degrees of polymerization (DP) and partial discharge (PD). Evaluation of oil-paper aging was based on statistical operators of PD and factor analysis was used to extract the principle parameters of PD. Three types of fuzzy clustering approaches were used to classify PD of aged oil-paper: the fuzzy c-means, the kernel fuzzy c-means, and the possibilistic fuzzy c-means. The clustering results showed that the possibilistic fuzzy c-means clustering was capable of classifying PD of oil-paper bound gas cavity specimens. The factor analysis method was also verified to be helpful in fuzzy clustering of PD data samples by reducing number of parameters.

In this paper, we describe the development of a system for evaluating an specific quality characteristic of recycled paper sheets using techniques of image analysis and pattern recognition. We call Bumpiness the phenomenon of interest, which is new in the literature on paper quality. This phenomenon is characterized by the appearance of macroscopic undulations on the paper sheet surface that may emerge shortly or some time after its production. We explore the detection and measurement of this defect by means of computer vision and statistical pattern recognition techniques that may allow early detection at the production site. Our goal is to give an scalar continuous measure of Bumpiness. We propose features computed from Gabor filter banks (GFB) and discrete wavelet transforms (DWT) for the characterization of paper sheet surface Bumpiness in recycled paper images. The starting point is to state the problem as a classification of the paper sheet images into two classes: low and high Bumpiness. In this setting we obtain, with both proposed texture modelling approaches (GFB and DWT), classification accuracies comparable to the agreement between human observers. The best performance is obtained using DWT features. Finally, we propose as the scalar index of Bumpines the fisher discriminant analysis (FDA) function defined on the space of the best features for the classification task. We perform an innovative validation process of this Bumpiness index, based on the ordering of random pairs of images, obtaining a very high agreement with the human observers.

This paper presents an empirical study to investigate the use of photometric stereo (PS) for micro-scale 3D measurement of paper samples. PS estimates per-pixel surface orientation from images of a surface captured from the same viewpoint but under different illumination directions. Specifically, we investigate the surface properties of paper to test whether they are sufficiently well approximated by a Lambertian reflectance model to allow veridical surface reconstruction under PS and explore the range of conditions for which this model is valid. We present an empirical setup that is used to conduct a series of experiments in order to analyse the applicability of PS at the micro-scale. In addition, we determine the best 4, 6, and 8 light source tilt (illumination) angles with respect to multi-source micro-scale PS. Furthermore, an intensity based image registration method is used to test the accuracy of the recovery of surface normals. The results demonstrate that at the micro-scale: (a) Lambert model represents well the data sets with low root mean square (RMS) error between the original and reconstructed image, (b) increasing the light sources from 4 to 8 reduces RMS error, and (c) PS can be used to extract veridical surface normals.

This paper puts across the various approaches and methods that have been proposed in the context of Fuzzy Mathematical Morphology. The underlying principles of Dilation & Erosion, the structuring elements used in various techniques, the unique variations put forth by researchers, new applications in spatial relationships, decision making, segmentation of medical images have been discussed.

Three perspectives were devised to characterize Chinese ink blurring, namely the ink absorption, the unevenness of the outlines at the blurring heads, and the difference of the tones at the blurring heads. Laboratory handsheets from softwood kraft pulp, having various basis weights, were prepared with or without wet pressing. They were soaked in Chinese ink for various times as the Klemm method. After drying, they were scanned by an image scanner set at 800 dpi to prepared bit-mapped images. These images were changed to binary images. Using the obtained images, various blurring indices based on the three perspectives were introduced. The blurring indices based on the ink absorption, the adsorbed ink amount and the capillary rise, for the handsheets without wet pressing were larger than those for the handsheets with wet pressing. Other blurring indices showed few differences between these papers with or without wet pressing. Thus, the three perspectives have different character in blots evaluation.

The study used the simulated e-paper to investigate how the bending radius of curvature (−10 cm, plane, and 10 cm) and 12 text/background color-combinations of e-paper affect subjects’ visual performance and subjective preference under various ambient illuminance conditions (200 and 500 lx). Analysis results indicated that the bending curvature and ambient illuminance did not significantly affect subjects’ visual performance. However, subjects visual performance differed significantly for different text/background color combinations of the simulated e-paper. When the background color of the simulated e-paper was set to yellow-like condition and the luminance of the text was low (2.2 and 4.6 cd/m 2 ), subjects’ visual performance was best. Regarding the subjective preferences of subjects, the results of this research also demonstrated that the bending curvature, text/background color combinations and ambient illuminance all significantly affected the subjective preferences of subjects. Subjects exhibited the best preference under the following settings: bending curvature of the simulated e-paper set to plane; background color of the simulated e-paper set to yellow-like condition and low text luminance (2.2 or 4.6 cd/m 2 ); high ambient illuminance (500 lx).

Two players of Rock-Paper-Scissors are modeled as adaptive agents which use a reinforcement learning algorithm and exhibit chaotic behavior in terms of trajectories of probability in mixed strategies space. This paper demonstrates that an external super-agent can exploit the behavior of the other players to predict favorable moments to play against one of the other players the symbol suggested by a sub-optimal strategy. This third agent does not affect the learning process of the other two players, whose only goal is to beat each other. The choice of the best moment to play is based on a threshold associated with the Local Lyapunov Exponent or the Entropy, each computed by using the time series of symbols played by one of the other players. A method for automatically adapting such a threshold is presented and evaluated. The results show that these techniques can be used effectively by a super-agent in a game involving adaptive agents that exhibit collective chaotic behavior.

The increased use of CRT monitors for displaying and controlling stimuli in studies of surface color poses problems of comparability with data obtained with traditional paper-and-illuminant methods. A review of comparable studies using the two methodologies revealed that CRT studies tend to report larger contrast effects. To investigate factors that may be responsible for this difference, simultaneous lightness contrast was measured using both CRT and paper-and-illuminant presentations. The spatial distribution of luminance in the whole field of view and the visual angles subtended by the displays were controlled. The CRT presentation yielded contrast effects twice as big as those measured for a paper surface in a homogeneously illuminated room. However, a paper display under Gelb lighting yielded almost exactly the same effect size as that measured in the CRT presentation. These results demonstrate that contrast effects in both modes of presentation are affected by the spatial distribution of luminance beyond the basic experimental stimuli.

In order to study the human color vision characteristics, the small color-difference discrimination threshold experiment at the 17 basic CIE color centers of high range of gloss color printed samples. A panel of 10 observers with normal color vision performed the visual assessment to 510 pairs of samples using admissibility method. The evaluation data of visual color-difference were obtained in CIELAB color space. The detailed comparision indicated that the data were used evaluate the four common color-difference formula, CIELAB, CIE94, CMC and CIEDE2000. The detailed analysis indicated that CIELAB recommended by CIE Performanced the best among the four modern color difference. For predicting very small color datas. The experimental data provides references for the improvement of uniform color space and color-difference formula.

In this paper we present a new semantics, called Local Models Semantics, and use it to provide a foundation to reasoning with contexts. This semantics captures and makes precise the two main intuitions underlying contextual reasoning: (i) reasoning is mainly local and uses only part of what is potentially available (e.g., what is known, the available inference procedures), this part is what we call context (of reasoning); however (ii) there is compatibility among the reasoning performed in different contexts. We validate our semantics by formalizing two important forms of contextual reasoning: reasoning with viewpoints and reasoning about belief.

Stripes are important features for scrap paper images mosaics. The stripe feature extraction can directly affect the effect of mosaics. A method of stripe feature extraction from scrap paper images is proposed in this paper. In order to obtain the background binary image, the original scrap paper images are firstly carried out by close operation and binarization. Secondly, the single pixel edges are extracted by using edge detection operator. Finally, the crossing points of stripes and the boundary of the background are detected by using the Progressive Probabilistic Hough Transformation. The length, angle and direction features of stripes are also extracted during this process. The experimental results show that the method of stripe feature extraction proposed in this paper is reasonable. By using this method the stripe features can be extracted from scrap paper images quickly and correctly. It provides features for the subsequent image mosaics.