A Method for Automatic Image Rectification and Stitching for Vehicle Yaw Marks Trajectory Estimation

The aim of this study has been to propose a new method for automatic rectification and stitching of the images taken on the accident site. The proposed method does not require any measurements to be performed on the accident site and thus it is frsjebalaee of measurement errors. The experimental investigation was performed in order to compare the vehicle trajectory estimation according to the yaw marks in the stitched image and the trajectory, reconstructed using the GPS data. The overall mean error of the trajectory reconstruction, produced by the method proposed in this paper was 0.086 m. It was only 0.18% comparing to the whole trajectory length.</p

A Novel Gaussian Extrapolation Approach for 2D Gel Electrophoresis Saturated Protein Spots

Analysis of images obtained from two-dimensional gel electrophoresis (2D-GE) is a topic of utmost importance in bioinformatics research, since commercial and academic software available currently has proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this work, we present an effective technique for the detection and the reconstruction of over-saturated protein spots. Firstly, the algorithm reveals overexposed areas, where spots may be truncated, and plateau regions caused by smeared and overlapping spots. Next, it reconstructs the correct distribution of pixel values in these overexposed areas and plateau regions, using a two-dimensional least-squares fitting based on a generalized Gaussian distribution. Pixel correction in saturated and smeared spots allows more accurate quantification, providing more reliable image analysis results. The method is validated for processing highly exposed 2D-GE images, comparing reconstructed spots with the corresponding non-saturated image, demonstrating that the algorithm enables correct spot quantificatio

Evaluation of EEG-based Complementary Features for Assessment of Visual Discomfort based on Stable Depth Perception Time

The investigation aimed at the evaluation of EEG activity during stereoscopic perception of images with different levels of visual comfort. Different levels of disparity and the number of details in stereoscopic views in some cases make it difficult to find the focus point for comfortable depth perception quickly. During our investigation, we found a tendency for differences in single sensor-based EEG signal activity at specific frequencies. A dataset of EEG signal records from 19 control subjects was collected and used for further evaluation. To support the reproducible research this dataset of EEG activity with associated subjective scores was made publicly available. During the experimental investigation, we found differences in EEG signal activity at different levels of visual comfort. In addition, the dynamics of EEG signal activity correlated to the moment of depth perception indication registered by the control subjects. The results of our investigation show that the ratio of alpha estimated from a single EEG sensor placed over the frontal lobe can serve as a complementary feature for the automatic detection of visually uncomfortable stereoscopic views

Exploring the Limits of Early Predictive Maintenance in Wind Turbines Applying an Anomaly Detection Technique

The aim of the presented investigation is to explore the time gap between an anomaly appearance in continuously measured parameters of the device and a failure, related to the end of the remaining resource of the device-critical component. In this investigation, we propose a recurrent neural network to model the time series of the parameters of the healthy device to detect anomalies by comparing the predicted values with the ones actually measured. An experimental investigation was performed on SCADA estimates received from different wind turbines with failures. A recurrent neural network was used to predict the temperature of the gearbox. The comparison of the predicted temperature values and the actual measured ones showed that anomalies in the gearbox temperature could be detected up to 37 days before the failure of the device-critical component. The performed investigation compared different models that can be used for temperature time-series modeling and the influence of selected input features on the performance of temperature anomaly detection.publishedVersio

Cascaded Multilevel Inverter-Based Asymmetric Static Synchronous Compensator of Reactive Power

The topology of the static synchronous compensator of reactive power for a low-voltage three-phase utility grid capable of asymmetric reactive power compensation in grid phases has been proposed and analysed. It is implemented using separate, independent cascaded H-bridge multilevel inverters for each phase. Every inverter includes two H-bridge cascades. The first cascade operating at grid frequency is implemented using thyristors, and the second one—operating at high frequency is based on the high-speed MOSFET transistors. The investigation shows that the proposed compensator is able to compensate the reactive power in a low-voltage three-phase grid when phases are loaded by highly asymmetrical reactive loads and provides up to three times lower power losses in the compensator as compared with the situation when the compensator is based on the conventional three-level inverters implemented using IGBT transistors.publishedVersio

Digital Signal Processing Tools

The laboratory manual on “Digital Signal Processing Tools” aims to stimulate acquirement of knowledge about modern means of digital signal processing, their operating principles and possibilities of application using MATLABTM. Problems and solutions of digital speech signal processing, modelling and synthesis as well as image segmentation and data classification are analysed. This publication has been produced with the financial assistance of Europe Social Fund and VGTU (Project No VP1-2.2-ŠMM-07-K-01-047). The book is a part of the project “The Essential Renewal of Undergraduates Study Programs of VGTU Electronics Faculty”

Treatment of over-saturated protein spots in two-dimensional electrophoresis gel images

Straipsnyje nagrinėjama baltymų pėdsakų atpažinimo ir parametrizavimo problema dvimatės elektroforezės gelių vaizduose. Pristatomas naujas būdas baltymų persisotinimams dvimatės elektroforezės gelių vaizduose aptikti ir rekonstruoti. Siūlomą paieškos ir rekonstravimo būdą sudaro keli etapai: gelio vaizdo paruošimas taikant naują medianos filtro kaukės dydžio parinkimo algoritmą, baltymų persisotinimų paieška taikant autorių siūlomus iškraipymų modelius, automatinis persisotinusio baltymų pėdsako išskyrimas ir rekonstravimas. Straipsnyje pateikti eksperimentinio tyrimo rezultatai įrodo, kad siūlomas būdas leidžia atpažinti iki 96% baltymų persisotinimų gelių vaizduose taikant vieną iš dviejų autorių siūlomų iškraipymų modelių. Baltymų persisotinimų rekonstravimui straipsnyje siūlomi nauji baltymų pėdsakų modeliai, gebantys tiksliau ir sparčiau atstatyti baltymo pėdsako formų nei alternatyvusis difuzinis modelis.The paper addresses the over-saturated protein spot detection and extraction problem in two-dimensional electrophoresis gel images. The effective technique for detection and reconstruction of over-saturated protein spots is proposed. The paper presents. an algorithm of the median filter mask adaptation for initial filtering of gel image, the models of over-saturation used for gel image analysis; several models of protein spots used for reconstruction, technique of the automatic over-saturated protein spot search and reconstruction. Experimental investigation confirms that proposed search technique lets to find up to 96% of over-saturated protein spots Moreover the proposed flexible protein spot shape models for reconstruction are faster and more accurate in comparison to the flexible diffusion model

Dviejų kamerų tarpusavio padėties įtaka trimačių vaizdų rekonstrukcijai

Pastaraisiais metais ypač daug dėmesio skiriama trimačių objektų atpažinimui, vaizdų rekonstrukcijai. Kuriami robotai, suvokiantys aplinką kameromis, analizuojant gaunamus vaizdus. Straipsnyje nagrinėjamas dviejų kamerų išdėstymo uždavinys. Keičiamas kampas tarp dviejų kamerų (jų centrinių ašių) ir analizuojama kamerų išdėstymo įtaka pirmiesiems trimačių vaizdų rekonstrukcijos etapams. Patogiausias yra lygiagretus kamerų išdėstymas, kai abiejų kamerų filmuojami taškai yra vienoje plokštumoje, tačiau trimačių vaizdų rekonstrukcijos metu dėl vidinių ir išorinių veiksnių pasitaiko nemažai klaidų, iškraipymų. Jų įtaką galima sumažinti priartinus stebimą objektą arčiau kamerų ir sumažinus kampą tarp jų. Keičiant kampą tarp kamerų, kinta objekto paviršiaus stebėjimo kampas. Šiame straipsnyje parodyta, kad net esant pakankamai dideliam kampui (60°–80°) galima gauti iki 20 % naudingų būdingųjų taškų, kuriuos suranda parinktas algoritmas

Reconstruction of overlapped protein spots using RBF networks

Detection and quantification of proteins in two-dimensional electrophoresis gel images is complicated but the same time important task for the development of modern diagnostics and prognostics systems. In this paper the solution of effective protein spot segmentation in two-dimensional electrophoresis gel images is proposed. It is based on the reconstruction of protein spots that are overlapping by the use of modified RBF network. The Anisotropic Gaussian Function with a tilt is proposed for individual protein spot shape model and as the basis function for modified RBF network. By experimentation modified RBF network is proven to be superior to watershed transformation and shape modeling based approaches. The modified RBF network in comparison to watershed transformation separates overlapped spots with the same accuracy in up to two times shorter distance between spots. At the same time computational load of usual and modified RBF networks differs insignificantly