Study of Camera Spectral Reflectance Reconstruction Performance using CPU and GPU Artificial Neural Network Modelling

Reconstruction of reflectance spectra from camera RGB values is possible, if characteristics of the illumination source, optics and sensors are known. If not, additional information about these has to be somehow acquired. If alongside with pictures taken, RGB values of some colour patches with known reflectance spectra are obtained under the same illumination conditions, the reflectance reconstruction models can be created based on artificial neural networks (ANN). In Matlab, multilayer feedforward networks can be trained using different algorithms. In our study we hypothesized that the scaled conjugate gradient back propagation (BP) algorithm when executed on Graphics Processing Unit, is very fast, but in terms of convergence and performance, it does not match Levenberg-Marquardt algorithm (LM), which, on the other hand, executes only on CPU and is therefore much more time-consuming. We also presumed that there exists a correlation between the two algorithms and is manifested through a dependency of MSE to the number of hidden layer neurons, and therefore the faster BP algorithm could be used to narrow the search span with the LM algorithm to find the best ANN for reflectance reconstruction. The conducted experiment confirmed speed superiority of the BP algorithm but also confirmed better convergence and accuracy of reflectance reconstruction with the LM algorithm. The correlation of reflectance recovery results with ANNs modelled by both training algorithms was confirmed, and a strong correlation was found between the 3rd order polynomial approximation of the LM and BP algorithm\u27s test performances for both mean and best performance

Implementation of Wiener Algorithm for Spectral Reflectance Reconstruction of 3 and 6 Channel Images

Wiener estimation is a widely used technique for the spectral reflectance reconstruction of colored objects. In our study the reflectance estimation of 3-channel images acquired using traditional RGB camera was compared with that of 6-channel images captured by a modified 6-channel camera. 240 patches of ColorChecker DC Chart were used for training and testing of the models.Their performance was assessed via quality metrics PSNR, RMSE and CIE DE2000 based on the reconstructed and spectrophotometrically measured reflectance values. Compared to the 3-channel models, 6-channel models in general provided better results. Lowest color difference CIE DE2000 was obtained when using 10 calculation terms in the 3-channel algorithm and 13 terms in the 6-channel. Best reconstruction models, i.e. lowest CIE DE2000 and RMSE and highest PSNR values, were found for the skin and neutral tones while the performance was the poorest with the saturated color patches. The obtained results can be of use in various practical applications, such as in a printing workflow with high precision color rendering or for accurate digitization of paintings and other works of art

Rich media mobile advertising: comparison of gestures used for navigation through a photo gallery

Cilj ovoga članka je ustanoviti preferencije korisnika u različitim interakcijama s obavijestima na prenosivom telefonu. Posebno nas je zanimalo da li korisnici više vole potezanje prstom (swiping) ili kuckanje (tapping) dok pregledavaju foto galeriju. Analizirala se korelacija između korisnikovog sučelja i angažmana (broja pregledanih fotografija). Dijelu korisnika je također pokazana obavijest s uputstvom kako postupati da bi se ustanovilo je li smanjenje mogućnosti izbora poboljšava korisnikovu funkcionalnost. Kako bismo odgovorili na ova pitanja razvili smo sustav praćenja u svrhu analize ponašanja 663 korisnika i anketirali 46 korisnika. Rezultati pokazuju da kod pregledavanja galerije potezanje prstom ima prednost pred kuckanjem i da način navigacije uistinu utječe na broj pregledanih fotografija. Također smo mogli pokazati da je postojanje upute smanjilo broj pogrešnih pokreta, ali smo predložili daljnje istraživanje kako bi se potpuno iskoristio njen potencijal.The aim of this paper was to get an insight into user’s preferences over different interactions with mobile ads. In particular, we were interested whether the users prefer swiping or tapping while navigating through a photo gallery. A correlation between the user interface and user engagement (the number of photos viewed) was analysed. A subset of users were also shown a coach notice with an information about how to navigate to examine whether coach notices can improve user experience by reducing usability issues. To answer these questions we developed a tracking system to analyse behaviour of 633 users and performed a survey on 46 people. The results show that swiping is preferable to tapping when navigating through the gallery and that the navigation mode does have an impact on the number of photos viewed. We were also able to show that the presence of a coach notice decreased the number of faulty gestures, but suggested a further work to maximize its potential

Performance Assessment of Three Rendering Engines in 3D Computer Graphics Software

The aim of the research was the determination of testing conditions and visual and numerical evaluation of renderings made with three different rendering engines in Maya software, which is widely used for educational and computer art purposes. In the theoretical part the overview of light phenomena and their simulation in virtual space is presented. This is followed by a detailed presentation of the main rendering methods and the results and limitations of their applications to 3D objects. At the end of the theoretical part the importance of a proper testing scene and especially the role of Cornell box are explained. In the experimental part the terms and conditions as well as hardware and software used for the research are presented. This is followed by a description of the procedures, where we focused on the rendering quality and time, which enabled the comparison of settings of different render engines and determination of conditions for further rendering of testing scenes. The experimental part continued with rendering a variety of simple virtual scenes including Cornell box and virtual object with different materials and colours. Apart from visual evaluation, which was the starting point for comparison of renderings, a procedure for numerical estimation and colour deviations of renderings using the selected regions of interest in the final images is presented

A multiparameter analysis of environmental gradients related to hydrological conditions in a binary karst system (underground course of the Pivka River, Slovenia)

Chemical and bacterial gradients under different hydrologi­cal conditions were studied in a well-developed underground karst system. Water samples were collected from the main un­derground drainage conduit of the Pivka River from October 2013 until June 2016. The system responds quickly to external pulses (precipitation events), and is also impacted by human interventions, as is demonstrated mainly by fluctuations of sul­phates, chlorides, and occasionally elevated concentrations of organic and faecal pollutants. Chemical and bacterial param­eters showed a monotonous trend of decreasing concentrations from the ponor towards the interior of the karst massif during stable hydrological conditions, and a significant change dur­ing high water conditions. High flow events tend to equilibrate chemical and bacterial parameters in the underground river. Concentrations of chlorides, TOC (total organic carbon) and nitrates were the most indicative parameters describing the for­mation of the gradient. Stable isotopes of hydrogen and oxygen in water indicated that the main karst conduit collects isotopi­cally different waters from the aquifer. The river water collected after nine kilometres of underground flow was always isotopically lighter than the waters collected from the upstream sites. Multiparameter analysis proved to be a useful tool for providing a more comprehensive understanding of the dynamics of the underground water, which influence both the underground environment and the ecology of the biome.Key words: karst, hydrology, water chemistry, nutrients, stable isotopes, PCA, bacteria. Multiparametrska analiza okoljskih gradientov, povezanih s hidrološkimi razmerami v binarnem kraškem sistemu (podzemni tok reke Pivke, Slovenija)V dobro razvitem podzemnem kraškem sistemu smo pri različnih hidroloških pogojih preučevali kemijske in bakterijske gradiente. Vzorce vode smo odvzeli iz glavnega podzemnega toka reke Pivke med oktobrom 2013 in junijem 2016. Sistem se hitro odziva na zunanje impulze (padavinski dogodki) in je tudi podvržen človekovim posegom, kar dokazujejo predvsem nihanja v koncentraciji sulfatov in kloridov ter občasno povišane koncentracije organskih in fekalnih onesnaževal. Spremljanje kemijskih in bakterijskih parametrov v stabilnih hidroloških razmerah je pokazalo monotoni trend zniževanja koncentracij od ponora proti notranjosti kraškega masiva. Razmere se izrazito spremenijo v času visokih vod, ko pride v podzemnem vodotoku do izenačenja tako kemijskih kot bakterijskih parametrov. Kloridi, TOC (skupni organski ogljik) in nitrati so bili najbolj indikativni parametri za opis nastanka gradienta. Stabilni izotopi vodika in kisika v vodi so pokazali, da vodotok glavnega kraškega kanala zbira izotopsko različne vode iz vodonosnika. Voda podzemne reke po devetih kilometrih toka v podzemlju je bila vedno izotopsko lažja kot vode iz gorvodno vzorčevanih mest. Multiparametrska analiza se je izkazala kot uporabno orodje za celovitejše razumevanje dinamike podzemnih voda, ki vpliva tako na podzemno okolje kot ekologijo bioma.Ključne besede: kras, hidrologija, kemija vode, hranila, stabilni izotopi, PCA, bakterije

The influence of ink concentration and layer thickness on yellow colour reproduction in liquid electrophotography toner

U elektrofotografiji s tekućem tonerom, kolornigamut je često smanjen u žutom području što vodi do problema pri realizaciji otisaka fotografske kvalitete. Poznato je da koncentracija čestica pigmenta u tiskarskom bojilu i debljina nanosa na papirnatoj podlozi utjeću na konačnu kvalitetu otiska. U ovom radu varirana su upravo ta dva parametara, primjenjujući pritom žuto ElectroInk procesno bojilo te elektrofotografski tiskarski stroju HP Indigo. Za kolorimetrijsku i slikovnu analizu primjenjena je ECI tiskovna forma koja sadrži 378 definiranih polja. Dobiveni rezultati statistički su obrađeni metodom dvosmjerne analize varijacija. Studija je prikazana pomoću volumena kolornog gamuta, te površinske pokrivenost rasterskih elemenata (točkica). U radu je utvrđeno je da na kvalitetu obojenja prvenstveno utječe debljina nanosa žutog bojila, dok je utjecaj koncentracije žutih pigmenata minoran. Povećanje nanosa bojila sa jedanog na dva imalo je mnogo jači učinak od onog koji je realiziran povećanjem sa dva sloja na tri sloja.In liquid toner electrophotography, colour gamut is often diminished in the yellow region leading to problems with photo quality prints. It is known that the concentration of pigment particles in the printing ink and its thickness when applied on a paper substrate decisively influence final print quality. Variation of these two parameters for the yellow process ink was performed by modifying the printing process of the electrophotographic printer HP Indigo S1000. Printed colour patches of ECI test chart were analysed colorimetrically and using image analysis approach. Two-way analysis of variance was implemented to statistically assess the obtained results. Both studied responses – colour gamut volume and area coverage of halftone dots – were found to be primarily influenced by the yellow ink layer thickness and much less by the ink concentration. Increase from one to two ink layers had a significantly stronger effect on each of the two responses when compared to an additional increase from two to three layers

Application of Fragrance Microcapsules onto Cotton Fabric after Treatment with Oxygen and Nitrogen Plasma

Cotton fabric was exposed to low-pressure capacitively coupled plasma to enhance the adsorption and adhesion of fragrance microcapsules (FCM). Two plasma-forming gases, namely oxygen (O2) and nitrogen (N2), were investigated. The untreated and plasma-treated samples were investigated for their morphological changes by scanning electron microscopy (SEM), mechanical properties (breaking force, elongation, and flexural rigidity), and wicking properties. The cotton samples were functionalized with FCM and the effect of plasma pretreatment on the adsorption and adhesion of FCM was evaluated using SEM, air permeability, fragrance intensity of unwashed and washed cotton fabrics, and Fourier transform infrared spectroscopy (FTIR). The results show that the plasma containing either of the two gases increased the wicking of the cotton fabric and that the O2 plasma caused a slight etching of the fibers, which increased the tensile strength of the cotton fabric. Both plasma gases caused changes that allowed higher adsorption of FCM. However, the adhesion of FCM was higher on the cotton treated with N2 plasma, as evidenced by a strong fragrance of the functionalized fabric after repeated washing

Exploiting Nonlinearity between Parallel Channels of Multiple Cameras for Accurate ANN Reconstruction of Reflectance Spectra

Colour of an observed object is unambiguously described by its reflectance. Translation from a colour description in RGB space obtained with a digital camera into reflectance, independent of illuminant and camera\u27s sensor characteristics, was performed through an artificial neural network (ANN). In the study, it was hypothesized that the ANN\u27s performance of reflectance reconstruction could be improved by using extended learning datasets with two or three cameras RGB input sets instead of one, but only if the parallel channels of cameras used are not linearly dependent. Nonlinearity was assessed by a quantitative measure of nonlinearity (QMoN), the metric primarily developed for use in chemistry. A noticeable reflectance performance improvement has been found with two and three cameras, even though the cameras\u27 parallel channels exerted only small degrees of nonlinearity. Close attention was paid to the impact of scattering of RGB readings around the ideal values on the reflectance reconstruction performance, and it has been found that the more pronounced scattering is inversely proportional to the performance of ANNs trained with a single-camera input learning set but shows no visible impact on the performance of ANNs trained with extended input learning sets

Comparison of Artificial Neural Network and Polynomial Approximation Models for Reflectance Spectra Reconstruction

Knowledge of surface reflection of an object is essential in many technological fields, including graphics and cultural heritage. Compared to direct multi- or hyper-spectral capturing approaches, commercial RGB cameras allow for a high resolution and fast acquisition, so the idea of mapping this information into a reflectance spectrum (RS) is promising. This study compared two modelling approaches based on a training set of RGB-reflectance pairs, one implementing artificial neural networks (ANN) and the other one using multivariate polynomial approximation (PA). The effect of various parameters was investigated: the ANN learning algorithm—standard backpropagation (BP) or Levenberg-Marquardt (LM), the number of hidden layers (HLs) and neurons, the degree of multivariate polynomials in PA, the number of inputs, and the training set size on both models. In the two-layer ANN with significantly fewer inputs than outputs, a better MSE performance was found where the number of neurons in the first HL was smaller than in the second one. For ANNs with one and two HLs with the same number of neurons in the first layer, the RS reconstruction performance depends on the choice of BP or LM learning algorithm. RS reconstruction methods based on ANN and PA are comparable, but the ANN models’ better fine-tuning capabilities enable, under realistic constraints, finding ANNs that outperform PA models. A profiling approach was proposed to determine the initial number of neurons in HLs—the search centre of ANN models for different training set sizes