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

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

Burst signal detector based on signal energy and standard deviation

Paper focuses on the spectrum sensing for cognitive radio solutions. The new algorithm is proposed for burst signal detection in frequency band where only this type of primary user signal appears (e.g. GSM band). Proposed spectrum sensor use signal energy and standard deviation estimates for primary user signal detection. A single perceptron is proposed to define a threshold for spectrum sensor. To investigate the efficiency of proposed spectrum sensor the real environment measurements were performe d in the frequency band used by GSM system for downlink . A n a dditional analysis of the signal energy estimates showed the periodicity of the energy changes in time domain. The calculation of FFT for signal energy changes in time has proven the performance of proposed spectrum detector for low power (situated far away from spectrum sensor) primary user signal detection in situations where it is covered by environment noise

Selection of an optimal adaptive filter for speech signal noise cancellation using C6455 DSP

This article discusses the implementation of the various adaptive filters for the filtering of the noisy speech signal, whose spectrum overlaps or is close to the information signal. Three types of adaptive filters are compared: LMS, NLMS and RLS. The computational load of the C6455 digital signal processor is monitored for different order filters and the efficiency of the filtering is measured using signal-to-noise ratio off the output signal. The results determined for the most suitable family of filters for application in real situations Ill. 8, bibl. 10 (in English; abstracts in English and Lithuanian)

mNet2FPGA: A Design Flow for Mapping a Fixed-Point CNN to Zynq SoC FPGA

The convolutional neural networks (CNNs) are a computation and memory demanding class of deep neural networks. The field-programmable gate arrays (FPGAs) are often used to accelerate the networks deployed in embedded platforms due to the high computational complexity of CNNs. In most cases, the CNNs are trained with existing deep learning frameworks and then mapped to FPGAs with specialized toolflows. In this paper, we propose a CNN core architecture called mNet2FPGA that places a trained CNN on a SoC FPGA. The processing system (PS) is responsible for convolution and fully connected core configuration according to the list of prescheduled instructions. The programmable logic holds cores of convolution and fully connected layers. The hardware architecture is based on the advanced extensible interface (AXI) stream processing with simultaneous bidirectional transfers between RAM and the CNN core. The core was tested on a cost-optimized Z-7020 FPGA with 16-bit fixed-point VGG networks. The kernel binarization and merging with the batch normalization layer were applied to reduce the number of DSPs in the multi-channel convolutional core. The convolutional core processes eight input feature maps at once and generates eight output channels of the same size and composition at 50 MHz. The core of the fully connected (FC) layer works at 100 MHz with up to 4096 neurons per layer. In a current version of the CNN core, the size of the convolutional kernel is fixed to 3×3. The estimated average performance is 8.6 GOPS for VGG13 and near 8.4 GOPS for VGG16/19 networks.This article belongs to the Section Artificial Intelligence Circuits and Systems (AICAS)This research is supported by Central Project Management Agency (Vilnius, Lithuania), project number 01.2.2-CPVA-K-703-02-0017