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Tytuł:
Comprehensive Evaluation Cloud Model for Ship Navigation Adaptability
Autorzy:
Zhu, M.
Wen, Y.
Zhou, C.
Xiao, C.
Powiązania:
https://bibliotekanauki.pl/articles/115973.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
cloud computing
Cloud Model
marine navigation
Delphi
Qualitative Description
Quantitative Transformation
Cloud Algorithm
Fuzzy Comprehensive Evaluation Method
Opis:
In this paper, using cloud model and Delphi, we build a comprehensive evaluation cloud model to solve the problems of qualitative description and quantitative transformation in ship navigation adaptability comprehensive evaluation. In the model, the normal cloud generator is used to find optimal cloud models of reviews and evaluation factors. The weight of each evaluation factor is determined by cloud model and Delphi. The floating cloud algorithm is applied to aggregate the bottom level’s evaluation factors, and comprehensive cloud algorithm is used to aggregate the highest level’s evaluation factors to get comprehensive evaluation cloud model. Finally, evaluation result is got by matching comprehensive evaluation cloud model and optimal cloud model of reviews. As case study, the model is applied to the small LNG ship’s navigation adaptability in Southeast Asia. Compared with the fuzzy comprehensive evaluation method, the model proposed in this paper is more intuitive and reliable in comprehensive evaluation of the small LNG ship’s navigation adaptability.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2014, 8, 3; 331-336
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Spreading information in distributed cloud systems using Gossip algorithm
Autorzy:
Barczak, A.
Barczak, M.
Powiązania:
https://bibliotekanauki.pl/articles/92860.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
distributed system
cloud system
gossip algorithm
Opis:
In a following article problem of a information sharing in distributed systemis described, as wellways of solving that problem with emphasize on Gossip protocol are presented. Furthermore the application has been creating allowing to test the Gossip protocol in a lab environment. Gossip protocol is highly parameterized and can be working in several modes. The main goal of the article is to examine the work of the Gossip algorithm, depending on the chosen mode and values of parameters, and analyses of a results.
Źródło:
Studia Informatica : systems and information technology; 2018, 1-2(22); 5-20
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Exploiting Dynamic Resource Allocation
Autorzy:
Geethamani, G. S.
Mayilvaganan, M.
Powiązania:
https://bibliotekanauki.pl/articles/1193583.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Cloud Computing
Multiprocessing
Neples Algorithm
Single Processing
Opis:
In recent years ad-hoc parallel data processing has emerged to be one of the killer applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud computing companies have started to integrate frameworks for parallel data processing in their product portfolio, making it easy for customers to access these services and to deploy their programs. However, the processing frameworks which are currently used have been designed for static, homogeneous cluster setups and disregard the particular nature of a cloud. Consequently, the allocated compute resources may be inadequate for big parts of the submitted job and unnecessarily increase processing time and cost. We discuss the opportunities and challenges for efficient parallel data processing in clouds and present our research project Nephele. Nephele is the first data processing framework to explicitly exploit the dynamic resource allocation offered by today’s IaaS clouds for both, task scheduling and execution. Particular tasks of a processing job can be assigned to different types of virtual machines which are automatically instantiated and terminated during the job execution. Based on this new framework, we perform extended evaluations of Map Reduce-inspired processing jobs on an IaaS cloud system and compare the results to the popular data processing framework Hadoop.
Źródło:
World Scientific News; 2016, 41; 253-260
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance of Routing Algorithm Remote Operation in Cloud Environment for IoT Devices
Autorzy:
Faychuk, Valentyn
Lavriv, Orest
Strykhalyuk, Bohdan
Shpur, Olga
Demydov, Ivan
Bak, Roman
Powiązania:
https://bibliotekanauki.pl/articles/226643.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
routing algorithm
IoT
IoT device
cloud environment
Opis:
This paper proposes an advanced routing method in the purpose of increasing IoT routing device’s power-efficiency, which allows to centralize routing tables computing as well as to push loading, related to routing tables computation, towards the Cloud environment at all. We introduced a phased solution for the formulated task. Generally, next steps were performed: stated requirements for the system with Cloud routing, proposed possible solution, and developed the whole system’s structure. For a proper study of the efficiency, the experiment was conducted using the developed system’s prototype for real-life cases, each represents own cluster size (several topologies by each size), used sizes are: 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27 and 29. Expectable results for this research – decrease the time of cluster’s reaction on topology changes (delay, needed to renew routing tables), which improves system’s adaptivity.
Źródło:
International Journal of Electronics and Telecommunications; 2019, 65, 3; 367-373
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Confidential Greedy Graph Algorithm
Autorzy:
Waszkiewicz, D.
Horubala, A.
Sapiecha, P.
Andrzejczak, M.
Powiązania:
https://bibliotekanauki.pl/articles/226681.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
cryptography
fully homomorphic encryption
confidential graph algorithm
cloud computing
Opis:
Confidential algorithm for the approximate graph vertex covering problem is presented in this article. It can preserve privacy of data at every stage of the computation, which is very important in context of cloud computing. Security of our solution is based on fully homomorphic encryption scheme. The time complexity and the security aspects of considered algorithm are described.
Źródło:
International Journal of Electronics and Telecommunications; 2018, 64, 2; 179-183
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Resource optimisation in cloud computing: comparative study of algorithms applied to recommendations in a big data analysis architecture
Autorzy:
Ndayikengurukiye, Aristide
Ez-Zahout, Abderrahmane
Aboubakr, Akou
Charkaoui, Youssef
Fouzia, Omary
Powiązania:
https://bibliotekanauki.pl/articles/2141815.pdf
Data publikacji:
2021
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
cloud computing
Big Data
IoT
recommender system
KNN algorithm
Opis:
Recommender systems (RS) have emerged as a means of providing relevant content to users, whether in social networking, health, education, or elections. Furthermore, with the rapid development of cloud computing, Big Data, and the Internet of Things (IoT), the component of all this is that elections are controlled by open and accountable, neutral, and autonomous election management bodies. The use of technology in voting procedures can make them faster, more efficient, and less susceptible to security breaches. Technology can ensure the security of every vote, better and faster automatic counting and tallying, and much greater accuracy. The election data were combined by different websites and applications. In addition, it was interpreted using many recommendation algorithms such as Machine Learning Algorithms, Vector Representation Algorithms, Latent Factor Model Algorithms, and Neighbourhood Methods and shared with the election management bodies to provide appropriate recommendations. In this paper, we conduct a comparative study of the algorithms applied in the recommendations of Big Data architectures. The results show us that the K-NN model works best with an accuracy of 96%. In addition, we provided the best recommendation system is the hybrid recommendation combined by content-based filtering and collaborative filtering uses similarities between users and items.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2021, 15, 4; 65-75
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Smart wireless sensor network and configuration of algorithms for condition monitoring applications
Autorzy:
Uhlmann, E.
Laghmouchi, A.
Geisert, C.
Hohwieler, E.
Powiązania:
https://bibliotekanauki.pl/articles/99644.pdf
Data publikacji:
2017
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
condition monitoring
data analysis
sensor network
algorithm
MEMS sensor
cloud
Opis:
Due to high demand on availability of production systems, condition monitoring is increasingly important. In recent years, the technical development have improved for realization of condition monitoring applications as a result of technological progress in fields such as sensor technology, computer performance and communication technology. Especially, the approaches of Industrie 4.0 and the use of the Internet of Things (IoT) technologies offer high potential to implement condition monitoring solutions. The connection of several sensor data of components to the cloud allows the identification of anomalies or defect pattern, this information can be used for predictive maintenance and new data-driven business models in production industry. This paper illustrates a concept of a smart wireless sensor network for condition monitoring application based on simple electronic components such as the single-board computer Raspberry Pi 2 modules and MEMS (Micro-Electro-Mechanical Systems) vibration sensors and communication standards MQTT (Message Queue Telemetry Transport). The communication architecture used for decentralized data analysis using machine learning algorithms and connection to the cloud is explained. Furthermore, a procedure for rapid configuration of condition monitoring algorithms to classify the current condition of the component is demonstrated.
Źródło:
Journal of Machine Engineering; 2017, 17, 2; 45-55
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Augmenting The Cloud Environment Security Through Blockchain Based Hash Algorithms
Autorzy:
Ravi Kanth, Motupalli
Krishna, Prasad K.
Powiązania:
https://bibliotekanauki.pl/articles/24083575.pdf
Data publikacji:
2023
Wydawca:
Politechnika Lubelska. Instytut Informatyki
Tematy:
cloud security
data privacy
data confidentiality
hash algorithm
substitutional encryption
Opis:
Many techniques and algorithms are developed to enhance the security in the cloud environment. This helps the users to secure their server from malicious attacks. Hence the study and investigation of the performance enhanced security algorithms is a must demanded field in the research industry. When large number users using same server to store their information in cloud environment security is a must needed component to preserve the privacy and confidentiality of every individual user. This can be further strengthened by detecting the attacks in earlier stages and taking countermeasure to prevent the attack. Thus securing the data network without any leakage and loss of the information is a challenging task in the cloud environment. When the attacks or intrusion is detected after the occurrence there may be damage to the data in the form of data damage or theft. Hence it is necessary to predict and detect the attacks before the occurrence to protect the privacy and confidentiality of the user information.
Źródło:
Journal of Computer Sciences Institute; 2023, 26; 1--6
2544-0764
Pojawia się w:
Journal of Computer Sciences Institute
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The testing of PCL: an open-source library for point cloud processing
Autorzy:
Zygmunt, M.
Powiązania:
https://bibliotekanauki.pl/articles/100450.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
Tematy:
terrestrial laser scanning
postprocessing
Point Cloud Library
algorithm
naziemny skaning laserowy
Opis:
In the era of the rapid development of the terrestrial laser scanning technology (TLS), that facilitates the acquisition of large data volumes in the form of three-dimensional point clouds, a need arises to create modern solutions to enable effective and efficient data processing. This paper presents the PCL (Point Cloud Library). This is an Open Source project that contains many of the key algorithms for TLS data, designed for filtering, registration, estimation of function, surface reconstruction, modeling and segmentation, as well as structures for identifying and matching objects. The article discusses the structure of the project as well as its most useful modules from the point of view of the TLS data processing. It describes the format used by the PCL data storage. Also, a practical example is enclosed, as a basis for the discussion of consecutive steps of working with the library, from recording input data in the correct format to visualization of the effects of the used algorithm.
Źródło:
Geomatics, Landmanagement and Landscape; 2013, 3; 105-115
2300-1496
Pojawia się w:
Geomatics, Landmanagement and Landscape
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cloud-based GNSS navigation spoofing detection
Autorzy:
Dobryakova, Larisa
Lemieszewski, Łukasz
Ochin, Evgeny
Powiązania:
https://bibliotekanauki.pl/articles/135509.pdf
Data publikacji:
2019
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
Cloud-based GNSS
GNSS
antiterrorism
antispoofing
transport safety
spoofer
spoofing detection algorithm
Opis:
Satellite navigation systems are commonly used to precisely determine the trajectory of transportation equipment. The widespread deployment of GNSS is pushing the current receiver technology to its limits due to the stringent demands for seamless, ubiquitous and secure/reliable positioning information. This fact is further aggravated by the advent of new applications where the miniaturized size, low power consumption and limited computational capabilities of user terminals pose serious risks to the implementation of even the most basic GNSS signal processing tasks. This paper has presented the advantage of Cloud-based GNSS Navigation, which facilitates the possibility of developing innovative applications where their particularities (e.g. massive processing of data, cooperation among users, security-related applications, etc.) make them suitable for implementation using Cloud-based infrastructure.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2019, 57 (129); 29-37
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using a vision cognitive algorithm to schedule virtual machines
Autorzy:
Zhao, J.
Mhedheb, Y.
Tao, J.
Jrad, F.
Liu, Q.
Streit, A.
Powiązania:
https://bibliotekanauki.pl/articles/330838.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
cloud computing
vision cognitive algorithm
VM scheduling
simulation
chmura obliczeniowa
algorytm poznawczy
szeregowanie
symulacja
Opis:
Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NP-hard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 535-550
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An ANN-based scalable hashing algorithm for computational clouds with schedulers
Autorzy:
Tchórzewski, Jacek
Jakóbik, Agnieszka
Iacono, Mauro
Powiązania:
https://bibliotekanauki.pl/articles/2055176.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
hashing algorithm
artificial neural network
scalable cryptography algorithm
computational cloud
task scheduler
algorytm haszowania
sztuczna sieć neuronowa
algorytm kryptograficzny
chmura obliczeniowa
Opis:
The significant benefits of cloud computing (CC) resulted in an explosion of their usage in the last several years. From the security perspective, CC systems have to offer solutions that fulfil international standards and regulations. In this paper, we propose a model for a hash function having a scalable output. The model is based on an artificial neural network trained to mimic the chaotic behaviour of the Mackey–Glass time series. This hashing method can be used for data integrity checking and digital signature generation. It enables constructing cryptographic services according to the user requirements and time constraints due to scalable output. Extensive simulation experiments are conduced to prove its cryptographic strength, including three tests: a bit prediction test, a series test, and a Hamming distance test. Additionally, flexible hashing function performance tests are run using the CloudSim simulator mimicking a cloud with a global scheduler to investigate the possibility of idle time consumption of virtual machines that may be spent on the scalable hashing protocol. The results obtained show that the proposed hashing method can be used for building light cryptographic protocols. It also enables incorporating the integrity checking algorithm that lowers the idle time of virtual machines during batch task processing.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 4; 697--712
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optical 3D scanning methods in biological research - selected cases
Metody skanowania optycznego 3D w badaniach biologicznych – opis przypadków
Autorzy:
Paśko, S.
Powiązania:
https://bibliotekanauki.pl/articles/3131489.pdf
Data publikacji:
2021
Wydawca:
Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
Tematy:
3D scanner
biological research
optical method
algorithm
measurement system
point cloud
marker
data analysis
Źródło:
Acta Scientiarum Polonorum. Zootechnica; 2021, 20, 1; 3-14
1644-0714
Pojawia się w:
Acta Scientiarum Polonorum. Zootechnica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automatyczna detekcja płaszczyzn w chmurze punktów w oparciu o algorytm RANSAC i elementy teorii grafów
RANSAC algorithm and elements of graph thory for automatic plane detection in 3D point cloud
Autorzy:
Poręba, M.
Goulette, F.
Powiązania:
https://bibliotekanauki.pl/articles/129757.pdf
Data publikacji:
2012
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
chmura punktów
segmentacja
RANSAC
graf
algorytm najbliższego sąsiada
etykietowanie
spójny komponent
point cloud
segmentation
graph
k-nearest neighbour algorithm
labelling
connected component
Opis:
Artykuł przedstawia metodę automatycznego wyodrębniania punktów modelujących płaszczyzny w chmurach punktów pochodzących z mobilnego bądź statycznego skaningu laserowego. Zaproponowany algorytm bazuje na odpornym estymatorze RANSAC umożliwiającym iteracyjną detekcję płaszczyzn w zbiorze cechującym się znacznym poziomem szumu pomiarowego i ilością punktów odstających. Aby zoptymalizować jego działanie, dla każdej wykrytej płaszczyzny uwzględniono relacje sąsiedztwa pomiędzy punktami przynależnymi. W tym celu zastosowano podejście oparte na teorii grafów, gdzie chmura punktów traktowana jest jako graf nieskierowany, dla którego poszukiwane są spójne składowe. Wprowadzona modyfikacja obejmuje dwa dodatkowe etapy: ustalenie najbliższych sąsiadów dla każdego punktu wykrytej płaszczyzny wraz z konstrukcją listy sąsiedztwa oraz etykietowanie spójnych komponentów. Rezultaty uzyskane pokazują iż algorytm poprawnie wykrywa płaszczyzny modelujące, przy czym niezbędny jest odpowiedni dobór parametrów początkowych. Czas przetwarzania uzależniony jest przede wszystkim od liczby punktów w chmurze. Nadal jednak aktualny pozostaje problem wrażliwości algorytmu RANSAC na niską gęstość chmury oraz nierównomierne rozmieszczenie punktów.
Laser scanning techniques play very important role in acquiring of spatial data. Once the point cloud is available, the data processing must be performed to achieve the final products. The segmentation is an inseparable step in point cloud analysis in order to separate the fragments of the same semantic meaning. Existing methods of 3D segmentation are divided into two categories. The first family contains algorithms functioning on principle of fusion, such as surface growing approach or split-merge algorithm. The second group consists of techniques making possible the extraction of features defined by geometric primitives i.e.: sphere, cone or cylinder. Hough transform and RANSAC algorithm (RANdom SAmple Consensus) are classified to the last of aforementioned groups. This paper studies techniques of point cloud segmentation such as fully automatic plane detection. Proposed method is based on RANSAC algorithm providing an iterative plane modelling in point cloud affected by considerable noise. The algorithm is implemented sequentially, therefore each successive plane represented by the largest number of points is separated. Despite all advantages of RANSAC, it sometimes gives erroneous results. The algorithm looks for the best plane without taking into account the particularity of the object. Consequently, RANSAC may combine points belonging to different objects into one single plane. Hence, RANSAC algorithm is optimized by analysing the adjacency relationships of neighbouring points for each plane. The approach based on graph theory is thus proposed, where the point cloud is treated as undirected graph for which connected components are extracted. Introduced method consists of three main steps: identification of k-nearest neighbours for each point of detected plane, construction of adjacency list and finally connected component labelling. Described algorithm was tested with raw point clouds, unprocessed in sense of filtration. All the numerical tests have been performed on real data, characterized by different resolutions and derived from both mobile and static laser scanning techniques. Obtained results show that proposed algorithm properly separates points for particular planes, whereas processing time is strictly dependent on number of points within the point cloud. Nevertheless, susceptibility of RANSAC algorithm to low point cloud density as well as irregular points distribution is still animportant problem. This paper contains literature review in subject of existing methods for plane detection in data set. Moreover, the description for proposed algorithm based on RANSAC, its principle, as well as the results is also presented.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2012, 24; 301-310
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Porównanie działania algorytmów aktywnego modelu TIN i predykcji liniowej do segmentacji punktów terenowych
Comparison of TIN active model and prediction of linear algorithms for terrain points segmentation
Autorzy:
Brodowska, P.
Powiązania:
https://bibliotekanauki.pl/articles/130626.pdf
Data publikacji:
2012
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
LIDAR
ALS
chmura punktów
algorytm aktywnego modelu TIN
predykcja liniowa
filtracja
segmentacja
lidar
point cloud
active TIN model algorithm
linear prediction
filtration
segmentation
Opis:
Istotną część punktów pozyskanych z wykorzystaniem technologii lotniczego skaningu laserowego stanowią odbicia od obiektów leżących ponad powierzchnią terenu np. drzew, krzewów czy budynków. Jednoznaczna i dokładna segmentacja jest kluczowym procesem pozwalającym na identyfikację obszarów homologicznych pod względem określonych własności w zbiorze punktów, co z kolei umożliwia generowanie NMT czy modelowanie brył budynków. W niniejszej pracy przedstawiono porównanie dwóch najczęściej stosowanych algorytmów filtracji chmury punktów ALS: aktywnego modelu TIN oraz predykcji liniowej. Badania wykonano dla wyodrębnionych 24 pól testowych charakteryzujących się różnym ukształtowaniem i użytkowaniem terenu. Weryfikacja wyników automatycznych filtracji polegała na ich porównaniu ze zbiorami referencyjnymi. W wyniku tego porównania określono względne procentowe błędy segmentacji punktów terenowych, które kształtowały się na poziomie od 0% do około 20% i zależne były od charakteru badanej powierzchni oraz obiektów na niej występujących. Przeprowadzone testy potwierdziły wysoką skuteczność obydwu badanych algorytmów, pokazując jednocześnie ich pewne ograniczenia i różnice w przypadku filtracji terenów o skomplikowanym ukształtowaniu lub pokryciu. Oba algorytmy zwracają podobny wynik w przypadku klasyfikacji chmury punktów opisujących tereny wykorzystywane rolniczo oraz tereny, na których zlokalizowane są pojedyncze budynki, krzewy i drzewa oraz parkingi z samochodami. Metoda oparta na predykcji liniowej lepiej eliminuje punkty zarejestrowane w wyniku odbicia wiązki lasera od podjazdów/wiaduktów/mostów, niż algorytm aktywnego modelu TIN.
A significant part of the data points obtained by using airborne laser scanning technology come from points reflected from objects situated above the ground such as trees, shrubs or buildings. Clear-cut and accurate segmentation is a crucial stage in data processing which allows to identify the homologous regions in terms of specific properties within a dataset of points, which further allows to generate DTM's or model building shapes. This paper shows an analysis of the two most commonly used algorithms for ALS point cloud filtering: active TIN model and linear prediction. The study was performed on 24 specifically extracted testing samples characterized by different topography and land use. The verification of the results of the automatic filtration process of both algorithms was based on comparison to reference datasets. As a result of this comparisons the relative percentage errors of automatic segmentation were determined. The level of the estimated errors varies from 0% to around 20% and depends on the characteristics of the land and the objects which are on the surface. The conducted study confirmed the high efficiency of both evaluated algorithms, at the same time revealing their limitations and differences in the filtration process for areas of a complex topography or terrain coverage. Both algorithms provide similar classification of point clouds describing land use for agriculture, areas on which a single building, shrub or tree is located, and for used car parks. Method based on linear prediction works better than active algorithm TIN model in terms of points recorded by the laser beam being reflected from vehicles/flyovers/bridges.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2012, 24; 63-71
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 17

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