Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Automatic coastline extraction from aerial images using edge detection and optimization procedures

Paravolidakis Vasileios

Simple record


URIhttp://purl.tuc.gr/dl/dias/DC1C2FBC-7B58-41FB-8224-E4B95227A8F8-
Identifierhttps://doi.org/10.26233/heallink.tuc.75951-
Languageen-
Extent71 pagesen
TitleAutomatic coastline extraction from aerial images using edge detection and optimization proceduresen
CreatorParavolidakis Vasileiosen
CreatorΠαραβολιδακης Βασιλειοςel
Contributor [Thesis Supervisor]Zervakis Michailen
Contributor [Thesis Supervisor]Ζερβακης Μιχαηλel
Contributor [Committee Member]Mania Aikaterinien
Contributor [Committee Member]Μανια Αικατερινηel
Contributor [Committee Member]Ragia Lemoniaen
Contributor [Committee Member]Ραγια Λεμονιαel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Electrical and Computer Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
Content SummaryNowadays, coastline detection and formation monitoring has become of high importance due to the increasing effects of climate change, global warming and rapid growth of human population on the morphological characteristics of coasts. Coastal areas play a significant role on the economy of an entire region especially in major tourist destinations, where tourist infrastructure has been developed in the last decades. This thesis addresses the problem of coastline extraction and morphological change monitoring/tracking in the course of decades. The proposed methodology presents an automatic coastline extraction algorithm, which utilizes grayscale aerial images. Our method is summarized in a four-step algorithm that enables robust extraction of the coastline. Specifically, the first step of our approach is a noise distortion reduction stage with the goal of ameliorating its impact on the input data. The subsequent step involves the application of a local threshold in the input image to segment it into a binary class image, land and sea. The result is then passed to the third stage of our approach, which applies morphological operators on the binary image, with the aim of removing small objects and preserving only the objects of interest. Finally in the last stage of our method, we perform edge detection and active contours fitting, in order to extract and model the coastline. The aforementioned algorithmic steps are illustrated through examples, which demonstrate the efficacy of the proposed methodology. The algorithm is also applicable to one band satellite imagery due to the fact they have same characteristics with grayscale aerial images.en
Type of ItemΔιπλωματική Εργασίαel
Type of ItemDiploma Worken
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-05-31-
Date of Publication2018-
SubjectImage processingen
Bibliographic CitationVasileios Paravolidakis, "Automatic coastline extraction from aerial images using edge detection and optimization procedures", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2018en
Bibliographic CitationΒασίλειος Παραβολιδάκης, "Automatic coastline extraction from aerial images using edge detection and optimization procedures", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2018el

Available Files

Services

Statistics