Tytuł: Interpolation merge as augmentation technique in the problem of ship classification

Autor/Autorzy: Dawid Połap, Marta Włodarczyk-Sielicka
 

Miejsce 
publikacji: Annals of Computer Science and Information Systems

Rok: 2020

Słowa 
kluczowe:

Abstrakt: Quite a common problem during training the classifier is a small number of samples in the training database, which can significantly affect the obtained results. To increase them, data augmentation can be used, which generates new samples based on existing ones, most often using simple transformations. In this paper, we propose a new approach to generate such samples using image processing techniques and discrete interpolation method. The described technique creates a new image sample using at least two others in the same class. To verify the proposed approach, we performed tests using different architectures of convolution neural networks for the ship classification problem.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://ieeexplore.ieee.org/document/9222849

DOI: 10.15439/2020F11

Tytuł: Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data

Autor/Autorzy: Marta Włodarczyk-Sielicka, Wioleta Blaszczak-Bak
 

Miejsce 
publikacji: SENSORS

Rok: 2020

Słowa 
kluczowe: big data applications, bathymetry, data reduction, data processing, data visualization, fusion of spatial data

Abstrakt: Floating autonomous vehicles are very often equipped with modern systems that collect information about the situation under the water surface, e.g., the depth or type of bottom and obstructions on the seafloor. One such system is the multibeam echosounder (MBES), which collects very large sets of bathymetric data. The development and analysis of such large sets are laborious and expensive. Reduction of the spatial data obtained from bathymetric and other systems collecting spatial data is currently widely used. In commercial programs used in the development of data from hydrographic systems, methods of interpolation to a specific mesh size are very frequently used. The authors of this article previously proposed original the true bathymetric data reduction method (TBDRed) and Optimum Dataset (OptD) reduction methods, which maintain the actual position and depth for each of the measured points, without their interpolation. The effectiveness of the proposed methods has already been presented in previous articles. This article proposes the fusion of original reduction methods, which is a new and innovative approach to the problem of bathymetric data reduction. The article contains a description of the methods used and the methodology of developing bathymetric data. The proposed fusion of reduction methods allows the generation of numerical models that can be a safe, reliable source of information, and a basis for design. Numerical models can also be used in comparative navigation, during the creation of electronic navigation maps and other hydrographic products.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://www.mdpi.com/1424-8220/20/21/6207

DOI: 10.3390/s20216207

Tytuł: Classification of Non-Conventional Ships Using a Neural Bag-Of-Words Mechanism

Autor/Autorzy: Dawid Polap, Marta Włodarczyk-Sielicka
 

Miejsce 
publikacji: SENSORS

Rok: 2020

Słowa 
kluczowe: bag-of-words mechanism, machine learning, image analysis, ship classification, marine system, river monitoring system, feature extraction

Abstrakt: The existing methods for monitoring vessels are mainly based on radar and automatic identification systems. Additional sensors that are used include video cameras. Such systems feature cameras that capture images and software that analyzes the selected video frames. Methods for the classification of non-conventional vessels are not widely known. These methods, based on image samples, can be considered difficult. This paper is intended to show an alternative way to approach image classification problems; not by classifying the entire input data, but smaller parts. The described solution is based on splitting the image of a ship into smaller parts and classifying them into vectors that can be identified as features using a convolutional neural network (CNN). This idea is a representation of a bag-of-words mechanism, where created feature vectors might be called words, and by using them a solution can assign images a specific class. As part of the experiment, the authors performed two tests. In the first, two classes were analyzed and the results obtained show great potential for application. In the second, the authors used much larger sets of images belonging to five vessel types. The proposed method indeed improved the results of classic approaches by 5%. The paper shows an alternative approach for the classification of non-conventional vessels to increase accuracy
 

Adres strony internetowej (link) do pełnego tekst publikacji: https://www.mdpi.com/1424-8220/20/6/1608/htm

DOI: 10.3390/s20061608

Tytuł: The Reduction Method of Bathymetric Datasets that Preserves True Geodata

Autor/Autorzy: Marta Włodarczyk-Sielicka, Andrzej Stateczny, Jacek Łubczonek

Miejsce
publikacji: Remote Sensing

Rok: 2019

Słowa
kluczowe: big data applications, data processing, data visualization, neural networks, reduction, coastal waters

Abstrakt:Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable to continuous transformations and they must be monitored and analyzed. Presently, bathymetric geodata are usually collected via modern hydrographic systems and comprise very large data point sequences that must then be connected using long and laborious processing sequences including reduction. As existing bathymetric data reduction methods utilize interpolated values, there is a clear requirement to search for new solutions. Considering the accuracy of bathymetric maps, a new method is presented here that allows real geodata to be maintained, specifically position and depth. This study presents a description of a developed method for reducing geodata while maintaining true survey values.

Adres strony internetowej (link) do pełnego tekstu
publikacji: https://www.mdpi.com/2072-4292/11/13/1610

DOI: 10.3390/rs11131610

Tytuł: Automatic Classification Using Machine Learning for Non-Conventional Vessels on Inland Waters

Autor/Autorzy: Marta Włodarczyk-Sielicka, Dawid Połap
 

Miejsce 
publikacji: SENSORS

Rok: 2019

Słowa 
kluczowe: machine learning, image analysis, feature extraction, ship classification, marine systems

Abstrakt: The prevalent methods for monitoring ships are based on automatic identification and radar systems. This applies mainly to large vessels. Additional sensors that are used include video cameras with different resolutions. Such systems feature cameras that capture images and software that analyze the selected video frames. The analysis involves the detection of a ship and the extraction of features to identify it. This article proposes a technique to detect and categorize ships through image processing methods that use convolutional neural networks. Tests to verify the proposed method were carried out on a database containing 200 images of four classes of ships. The advantages and disadvantages of implementing the proposed method are also discussed in light of the results. The system is designed to use multiple existing video streams to identify passing ships on inland waters, especially non-conventional vessels.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://www.mdpi.com/1424-8220/19/14/3051

DOI: 10.3390/s19143051

Tytuł: The Use of an Artificial Neural Network to Process Hydrographic Big Data during Surface Modeling

Autor/Autorzy: Marta Włodarczyk-Sielicka, Jacek Łubczonek

Miejsce
publikacji: Computers

Rok: 2019

Słowa
kluczowe: neural networks, bathymetric data, interpolation, reduction, DTM, big data

Abstrakt:At the present time, spatial data are often acquired using varied remote sensing sensors and systems, which produce big data sets. One significant product from these data is a digital model of geographical surfaces, including the surface of the sea floor. To improve data processing, presentation, and management, it is often indispensable to reduce the number of data points. This paper presents research regarding the application of artificial neural networks to bathymetric data reductions. This research considers results from radial networks and self-organizing Kohonen networks. During reconstructions of the seabed model, the results show that neural networks with fewer hidden neurons than the number of data points can replicate the original data set, while the Kohonen network can be used for clustering during big geodata reduction. Practical implementations of neural networks capable of creating surface models and reducing bathymetric data are presented.

Adres strony internetowej (link) do pełnego tekstu
publikacji: https://www.mdpi.com/2073-431X/8/1/26

DOI: 10.3390/computers8010026

Tytuł: Interpolating Bathymetric Big Data for an Inland Mobile Navigation System

Autor/Autorzy: Marta Włodarczyk-Sielicka, Natalia Wawrzyniak
 

Miejsce 
publikacji: Information Technology and Control

Rok: 2018

Słowa 
kluczowe: bathymetric data, interpolation method, maritime information systems, mobile systems

Abstrakt: Depth information is crucial in most navigational analysis and decision support implemented in existing inland navigation systems. Bathymetric data sets need to be preprocessed and converted into Digital Terrain Model (DTM) by interpolation methods to provide different vector layers for Electronic Navigational Chart. Data for inland waters need to be precise and valid due to quickly alternating inland environment and much shallower areas than on marine waters. At the same, time visual effect of created layers needs to be readable and easily interpreted by a navigator. In this paper, we analyse and assess the results obtained after using several interpolation methods for DTM building. The experiments used real inland data from bathymetric surveys conducted on the waters of Szczecin area. The main novelty of the research is the use of generally known interpolation algorithms during processing of bathymetric big data, which are the primary layer in new mobile system for inland navigation. The created depth contours are the base of navigational analysis provided by the mobile inland navigation system MOBINAV.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://itc.ktu.lt/index.php/ITC/article/view/19561

DOI: 10.5755/j01.itc.47.2.19561

Tytuł: Redukcja konfliktów graficznych dla obiektów punktowych w systemie mobilnej nawigacji śródlądowej

Autor/Autorzy: Marta Włodarczyk-Sielicka, Witold Kazimierski, Izabela Bodus-Olkowska

Miejsce
publikacji: Roczniki Geomatyki [Annals of Geomatics]

Rok: 2017

Słowa
kluczowe: konflikty graficzne, nawigacja mobilna, model prezentacji kartograficznej, nawigacja śródlądowa, generalizacja, graphic conflicts, mobile navigation, cartographic presentation model, inland shipping, generalization

Abstrakt: Mobilna nawigacja MOBINAV jest przykładem systemu informacji przestrzennej dedykowanego dla rekreacyjnych użytkowników śródlądowych dróg wodnych, realizowanego w ramach projektu badawczego pt. „Mobilna nawigacja śródlądowa”. Do głównych założeń projektu można zaliczyć opracowanie nowego modelu mobilnej prezentacji kartograficznej. W trakcie pracy nad modelem systemu, skupiono się na potrzebach użytkownika końcowego oraz możliwościach technicznych urządzeń mobilnych, których użycie wiąże się z ograniczeniami w wizualizacji danych na stosunkowo małych ekranach. Tak zdefiniowany model zakładał opracowanie niezależnych zestawów danych wykorzystywanych w poszczególnych geokompozycjach składowych, które powstały w wyniku generalizacji podstawowego zestawu danych. Dla obiektów o geometrii liniowej oraz powierzchniowej zastosowano klasyczne algorytmy upraszczania przy poszczególnych skalach wyświetlania map wynikowych. W trakcie wyświetlania obiektów punktowych, zwłaszcza punktów głębokości oraz znaków nawigacyjnych, które mają kluczowe znaczenie w trakcie prowadzenia nawigacji na ekranie urządzenia widoczna była zbyt duża ilość informacji, a przede wszystkim w niektórych miejscach symbole nakładały się na siebie. Konieczna jest, zatem korekta, polegająca na rozsunięciu sygnatur oraz ich dopasowaniu do skali wyświetlania. W artykule przedstawiono propozycję algorytmu wykrywania oraz usuwania konfliktów graficznych dla obiektów o geometrii punktowej dedykowanego budowanemu systemowi mobilnej nawigacji śródlądowej. Zawarto przykładowe wyniki dla poszczególnych skal wyświetlania mapy wynikowej na danych rzeczywistych zaimportowanych z dostępnych źródeł. Przeprowadzone testy pozwalają sądzić, iż zastosowanie przedstawionego w artykule algorytmu w znacznym stopniu ulepsza poprawną interpretację mapy na urządzeniu mobilnym.

Adres strony internetowej (link) do pełnego tekstu
publikacji: http://rg.ptip.org.pl/index.php/rg/article/view/RG2017-2-Wlodarczyk-SielickaKazimierskiBodus-Olkowska

DOI:

Tytuł: Simplification methods for line and polygon features in mobile navigation systems for inland waters

Autor/Autorzy: Marta Włodarczyk-Sielicka, Izabela Bodus-Olkowska
 

Miejsce 
publikacji: Zeszyty Naukowe Akademii Morskiej w Szczecinie

Rok: 2017

Słowa 
kluczowe: simplification, inland shipping, geodata integration, mobile systems

Abstrakt: Mobile navigation for inland shipping is an example of a GIS system dedicated for recreational users using inland waterways. Developing this system is a primary purpose of the research project “Mobile Navigation for Inland Waters” funded by the National Centre for Research and Development under the program LIDER. System assumptions include the development of a dedicated model of mobile cartographic presentation, taking into account the generalization of data. This article is focused on simplification of line and polygon features, included in the spatial data model MODEF (MObinav Data Exchange Format), which is used in the created system. During the simplification of line features, the Douglas-Peucker algorithm was mainly implemented. During the simplification of polygon features, a simplification method was applied, maintaining the basic shape and size of the objects. A simplification tolerance parameter and a parameter determining the minimum area of the object was also used. In addition, objects within a certain distance were merged. A smoothing tool for the shape and size of buildings and the PEAK method (Polynomial Approximation with Exponential Kernel) were used as well. Furthermore, a selection tool was employed and features with minor importance to the user were deleted during navigation mode. Given the requirements of the future user of the system, a separate model simplification for each of the layers of the system was created; these models are combinations of the methods listed above. The overriding factor that has been taken into account during the research of simplification methods, was the limitation of the sharpness of human eyes. The study of generalization methods was carried out in ArcGIS software.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://repository.am.szczecin.pl/handle/123456789/2395

DOI: 10.17402/223

Tytuł: Ocena przekazu kartograficznego mobilnej nawigacji śródlądowej MOBINAV

Autor/Autorzy: Izabela Bodus-Olkowska, Grzegorz Zaniewicz, Marta Włodarczyk-Sielicka
 

Miejsce 
publikacji: Roczniki Geomatyki [Annals of Geomatics]

Rok: 2017

Słowa 
kluczowe: nawigacja śródlądowa, nawigacja mobilna, mobilna kartografia, prezentacja kartograficzna

Abstrakt: Obecnie prawie codziennie każdy, kto posiada urządzenie typu smartphone, wspomaga się aplikacjami mapowymi, które we współpracy z wbudowanym modułem GPS umożliwiają łatwą lokalizację obiektów, wytyczenie trasy czy nawigowanie do celu. Aplikacja MOBINAV jest jedną z tego typu aplikacji, dedykowaną prowadzeniu nawigacji na wodach śródlądowych, w głównej mierze przez użytkowników rekreacyjnych. Przekaz kartograficzny aplikacji mobilnych jest dynamiczny i bardziej skomplikowany w porównaniu do tradycyjnego. Sama mapa zmienia się pod wpływem czynników zależnych od użytkownika i jego wymagań lub/oraz pod wpływem zdarzeń generowanych w trakcie realizacji nawigacji. Autorzy systemu MOBINAV opracowali model kartograficzny opierając się na dostępnych rozwiązaniach wprowadzonych w nawigacjach samochodowych lub pieszych oraz biorąc pod uwagę wymagania użytkowników, otrzymane na podstawie stosownej ankiety. Model ten zakłada 2 prezentacje kartograficzne ze względu na rodzaj urządzenia: smartphone/tablet oraz HUD. Na pierwszych prezentowana jest mapa wraz z wszystkimi jej komponentami, natomiast wizualizacja dla HUD zawiera elementy trasy jako główną treść przekazu kartograficznego. Pod pojęciem przekazu kartograficznego systemu MOBINAV należy rozumieć logikę treści, czyli dobór elementów składających się na treść mapy (geokompozycja) dla konkretnego przypadku użycia i w odpowiedniej skali oraz logika systemu znaków i symboli, czyli stylizacja mapy – doborem kolorów poszczególnych obiektów, projektem systemu znaków i symboli reprezentujących obiekty punktowe, przy zachowaniu zasady izomorfizmu treści i postaci. Efektywność, funkcjonalność i użyteczność przekazu kartograficznego systemu MOBINAV poddana została weryfikacji przez potencjalnych użytkowników aplikacji za pomocą ankiety internetowej. Wyniki ankiety pozwoliły na dokonanie pełnej oceny, wyciągnięcie wniosków oraz zaplanowanie dalszych prac nad rozwojem i udoskonaleniem aspektów aplikacji związanych z przekazem kartograficznym.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://rg.ptip.org.pl/index.php/rg/article/view/RG2017-1-Bodus-OlkowskaZaniewiczWlodarczyk-Sielicka

DOI:

Tytuł: TECHNOLOGY OF SPATIAL DATA GEOMETRICAL SIMPLIFICATION IN MARITIME MOBILE INFORMATION SYSTEM FOR COASTAL WATERS

Autor/Autorzy: Witold Kazimierski, Marta Włodarczyk-Sielicka

Miejsce
publikacji: Polish Maritime Research

Rok: 2016

Słowa
kluczowe: simplification, maritime information systems, mobile systems, generalization

Abstrakt: The paper undertakes the subject of spatial data pre-processing for marine mobile information systems. Short review of maritime information systems is given and the focus is laid on mobile systems. The need of spatial data generalization is underlined and the concept of technology for such generalization in mobile system is presented. The research part of the paper presents the results of analyzes on selected parameters of simplification in the process of creating mobile navigation system for inland waters. In the study authors focused on selected layers of system. Models of simplification for layers with line features and with polygons were tested. The parameters of tested models were modified for the purposes of study. The article contains tabular results with statistics and spatial visualization of selected layers for individual scales.

Adres strony internetowej (link) do pełnego tekstu
publikacji: http://www.bg.pg.gda.pl/pmr/pdf/PMRes_2016_3.pdf

DOI: 10.1515/pomr-2016-0026

Tytuł: Clustering Bathymetric Data for Electronic Navigational Charts

Autor/Autorzy: Marta Włodarczyk-Sielicka, Andrzej Stateczny
 

Miejsce 
publikacji: JOURNAL OF NAVIGATION

Rok: 2016

Słowa 
kluczowe: Electronic Chart Display and Information System, Bathymetry, Data reduction

Abstrakt: An electronic navigational chart is the primary source of information for the navigator. The component that contributes most significantly to the safety of navigation on water is the information on the depth of an area. For the purposes of this article, the authors use data obtained by the interferometric sonar GeoSwath Plus. The data were collected in the area of the Port of Szczecin. The samples constitute large sets of data. Data reduction is a procedure by which to reduce the size of a data set to make it easier and more effective to analyse. The main objective of the authors is the compilation of a new reduction algorithm for bathymetric data. The clustering of data is the first part of the search algorithm. The next step consists of generalization of bathymetric data. This article presents the comparison and analysis of results of clustering bathymetric data using the following selected methods: K-means clustering algorithm, traditional hierarchical clustering algorithms and self-organizing map (using artificial neural networks).
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=10421702&fileId=S0373463316000035

DOI: 10.1017/S0373463316000035

Tytuł: Mobile River Navigation for Smart Cities

Autor/Autorzy: Witold Kazimierski, Natalia Wawrzyniak, Marta Włodarczyk-Sielicka, Tomasz Hyla, Izabela Bodus-Olkowska, Grzegorz Zaniewicz

Miejsce
publikacji: Rozdział w książce Springer

Rok: 2019

Słowa
kluczowe: Mobile GIS, Mobile navigation, Smart rivers, Smart cities

Abstrakt: One of the main aspects of smart city is smart mobility, covering mainly smart transport solutions for users. On the other hand smart living includes also touristic attractiveness of the city and its information systems. The paper presents a mobile solution, which integrate both – supporting of smart transportation and touristic needs of the users. It is a system of mobile navigation for inland waters. The concept of the system is presented, followed by the methodological aspects of its designing and implementation. The mobility of system is presented in various aspects (spatial data integration, cartographic model and spatial analysis and implementation issues). Although the system may be independent technology, it is shown from the point of view of possible integration in wider smart city concept. In such approach the functional possibilities of the system are increased and smart city implementation may be also enhanced.

Adres strony internetowej (link) do pełnego tekstu
publikacji: https://link.springer.com/chapter/10.1007/978-3-030-30275-7_45

DOI: 10.1007/978-3-030-30275-7_45

Tytuł: Multibeam Echosounder and LiDAR in Process of 360-Degree Numerical Map Production for Restricted Waters with HydroDron

Autor/Autorzy: Andrzej Stateczny, Marta Włodarczyk-Sielicka, Grońska Daria, Weronika Motyl
 

Miejsce 
publikacji: Rozdział w książce

Rok: 2018

Słowa 
kluczowe: Sensors, Data visualization, Laser radar, Three-dimensional displays, Data models, Sonar

Abstrakt: In order to increase the safety of inland navigation and facilitate the monitoring of the coastal zone of restricted waters, a model of multi-sensory fusion of data from hydroacoustic and optoelectronic systems mounted on the autonomous survey vessel HydroDron will be developed. In the research will be used the LiDAR laser scanner and multibeam echosounder. To increase the visual quality and map accuracy, additionally side scan sonar and rotary camera have been used. The main purpose of the research is to create the concept to develop new models of data processing from sensors, their comprehensive fusion and consistent visualization. This will allow to present data in the form of 360 degrees spatial maps for coastal areas. This kind of map enables the visualization of spatial data both horizontally and vertically, creating one spherical image of the terrain surface. The high level of product innovation determines its potential for commercialization.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://ieeexplore.ieee.org/document/8453710

DOI: 10.1109/BGC-Geomatics.2018.00061

Tytuł: The Use of an Artificial Neural Network for a Sea Bottom Modelling

Autor/Autorzy: Jacek Łubczonek, Marta Włodarczyk-Sielicka

Miejsce
publikacji: Rozdział w książce

Rok: 2018

Słowa
kluczowe: Bathymetric data, Neural networks, Interpolation, Reduction, DTM, Big data

Abstrakt: Currently data are often acquired by using various remote sensing sensors and systems, which produce big data sets. One of important product are digital models of geographical surfaces that include the sea bottom surface. To improve their processing, visualization and management is often necessary reduction of data points. Paper presents research regarding the application of neural networks for bathymetric geodata reductions. Research take into consideration radial networks, single layer perceptron and self-organizing Kohonen network. During reconstructions of sea bottom model, results shows that neural network with less number of hidden neurons can replace original data set. While the Kohonen network can be used for clustering during reduction of big geodata. Practical implementation of neural network with creation of surface models and reduction of bathymetric data is presented.

Adres strony internetowej (link) do pełnego tekstu
publikacji: https://link.springer.com/content/pdf/10.1007%2F978-3-319-99972-2.pdf

DOI: 10.1007/978-3-319-99972-2_29

Tytuł: Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process

Autor/Autorzy: Marta Włodarczyk-Sielicka, Andrzej Stateczny
 

Miejsce 
publikacji: Rozdział w książce, Institute of Electrical and Electronics Engineers (IEEE)

Rok: 2017

Słowa 
kluczowe: big data, data processing, clustering methods, sea measurements

Abstrakt: The article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It consists of two steps: initial division of the area into a grid of squares and clustering using artificial neural networks. In the first step maximum level of division of the grid will be founded and its size will be determined. In the second step of fragmentation each square will be divided into clusters using Kohonen network. The experiments were performed on test areas with different slope of the bottom. The results and conclusion were presented.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://ieeexplore.ieee.org/document/8071471

DOI: 10.1109/BGC.Geomatics.2017.67

Tytuł:Problem of Bathymetric Big Data Interpolation for Inland Mobile Navigation System

Autor/Autorzy: Marta Włodarczyk-Sielicka, Natalia Wawrzyniak
 

Miejsce 
publikacji: Rozdział w książce, Springer

Rok: 2017

Słowa 
kluczowe: Bathymetric data, Interpolation method, Maritime information systems, Mobile systems

Abstrakt: Depth information is crucial in most navigational analysis and decision support implemented in existing inland navigation systems. Bathymetric data sets needs to be preprocessed and converted into Digital Terrain Model by interpolation methods to provide different vector layer for Electronic Navigational Chart. Data for inland waters needs to be precise and valid due to quickly alternating inland environment and much shallower areas than on marine waters. At the same time visual effect of created layers needs to be readable and easily interpreted by a navigator. In this paper authors analyze different interpolation method for DTM building from the perspective of accepted criteria. Created depth contours are the base of navigational analysis provided by mobile inland navigation system MOBINAV. The experiments used real inland data from bathymetric surveys conducted on waters of Szczecin area.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://link.springer.com/chapter/10.1007/978-3-319-67642-5_51

DOI: 10.1007/978-3-319-67642-5_51

Tytuł:MSIS sonar image segmentation method based on underwater viewshed analysis and high-density seabed model

Autor/Autorzy: Natalia Wawrzyniak, Marta Włodarczyk-Sielicka, Andrzej Stateczny
 

Miejsce 
publikacji: Rozdział w książce, Institute of Electrical and Electronics Engineers (IEEE)

Rok: 2017

Słowa 
kluczowe: Sonar, Sonar navigation, Transducers, Acoustic beams, Sea surface, Image segmentation

Abstrakt: High resolution images of Mechanically Scanned Imaging Sonars can bring detailed representation of underwater area if favorable conditions for acoustic signal to propagate are provided. However to properly asses underwater situation based solely on such data can be challenging for less than proficient interpreter. In this paper we propose a method to enhance interpretative potential of MSIS image by dividing it in to subareas depending on information about slope gradient and direction derived from high-density bathymetric model using viewshed analysis. Additional image channel is created to store data on adherence of sonar data into each class representing different information related to sea bed shape. The paper also contains details on segmentation algorithm using traditional image processing method.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://ieeexplore.ieee.org/document/8008210/

DOI: 10.23919/IRS.2017.8008210

Tytuł: General Concept of Reduction Process for Big Data Obtained by Interferometric Methods

Autor/Autorzy: Marta Włodarczyk-Sielicka, Andrzej Stateczny
 

Miejsce 
publikacji: Rozdział w książce, Institute of Electrical and Electronics Engineers (IEEE)

Rok: 2017

Słowa 
kluczowe: Sonar measurements, Big Data, Artificial neural networks, Sea measurements, Acoustic beams, Transducers

Abstrakt: Interferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data - datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main goal of new reduction method developed by the authors is that, the data after reduction will not be an interpolated value. The proposed method is consists of two main stage: the grouping of data and the generalization of data. The first stage consists of two steps: initial division and clustering. In the first step, the area will be divided into a grid of squares. The maximum level of generalization of the grid will be founded and its size will be defined. In the second step of data grouping, namely clustering artificial neural networks will be used. Artificial neural networks are good alternative to traditional methods of clustering data. The authors decided to use artificial intelligence methods during the processing of data obtained by interferometric methods because it is novel approach to such issues and provides satisfactory results. The author’s goal is to represent each group by a single sample depending on the compilation scale of final product. The article contains a detailed description of the proposed method.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: https://ieeexplore.ieee.org/document/8008212

DOI: 10.23919/IRS.2017.8008212

Tytuł: Importance of Neighborhood Parameters During Clustering of Bathymetric Data Using Neural Network

Autor/Autorzy: Marta Włodarczyk-Sielicka
 

Miejsce 
publikacji: Tekst popularnonaukowy, Springer International Publishing AG

Rok: 2016

Słowa 
kluczowe: Bathymetry, Data processing, Clustering, Artificial neural network

Abstrakt: The main component, which has a significant impact on safety of navigation, is the information about depth of a water area. The commonly used solution for depths measurement is usage the echosounders. One of the problems associated with bathymetric measurements is recording a large number of data. The fundamental objective of the author’s research is the implementation of a new reduction method for geodata to be used for the creation of bathymetric map. The main purpose of new reduction algorithm is that, the position of point and the depth value at this point will not be an interpolated value. In the article, author focused on importance of neighborhood parameters during clustering of bathymetric data using neural network (self-organizing map) – it is the first stage of the new method. During the use of Kohonen’s algorithm, the author focused on two parameters: topology and initial neighborhood size. During the test, several populations were created with number of clusters equal 25 for data collected from the area of 625 square meters (dataset contains of 28911 XYZ points). In the next step, statistics were calculated and results were presented in two forms: tabular form and as spatial visualization. The final step was their comprehensive analysis.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://link.springer.com/chapter/10.1007/978-3-319-46254-7_35

DOI: 10.1007/978

Tytuł: Comparison of Selected Reduction Methods of Bathymetric Data Obtained by Multibeam Echosounder

Autor/Autorzy: Marta Włodarczyk-Sielicka, Andrzej Stateczny
 

Miejsce 
publikacji: Tekst popularnonaukowy, IEEE Computer Society Conference Publishing Services

Rok: 2016

Słowa 
kluczowe: data processing, sonar measurements, reduction

Abstrakt: The publication presents a comparison of various methods to reduce datasets obtained by multibeam echo sounder. Data reduction is the process of minimizing the amount of data that needs to be stored in a data storage environment. Data reduction makes data easier and more effective for the purposes of the analysis. The authors decided to compare selected reduction method used in hydrography: GeoSwath Plus software and BathyDataBASE software. As the scale of the final product was applied 1: 2000. Selected parameters for each of the test methods have been adopted. After reduction of the points surfaces were created. In the next step these surfaces were compared and detailed analysis was conducted.
 

Adres strony internetowej (link) do pełnego tekstu 
publikacji: http://ieeexplore.ieee.org/document/7548008/

DOI: 10.1109/BGC

Tytuł: Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks

Autor/Autorzy: Marta Włodarczyk-Sielicka, Jacek Łubczonek, Andrzej Stateczny

Miejsce
publikacji: Tekst popularnonaukowy, IEEE Computer Society Conference Publishing Services

Rok: 2016

Słowa
kluczowe: bathymetry, interferometric system, artificial neural network, clustering algorithm

Abstrakt: The article presents a particular comparison of selected clustering algorithms of data obtained by interferometrie methods using artificial neural networks. For the purposes of the experiment original data from Szczecin Port have been tested. For collecting data authors used the interferometric sonar system GeoSwath Plus 250 kHz. GeoSwath Plus offers very efficient simultaneous swath bathymetry and side scan seabed mapping. During the use of Kohonen’s algorithm, the network, during learning, use the Winner Take All rule and Winner Take Most rule. The parameters of the tested algorithms were maintained at the level of default. During the research several populations were generated with number of clusters equal 9 for data gathered from the area of 100m2. In the subsequent step statistics were calculated and outcomes were shown as spatial visualization and in tabular form.

Adres strony internetowej (link) do pełnego tekstu
publikacji: http://ieeexplore.ieee.org/document/7497290/

DOI: 10.1109/IRS