Academic Journal
Automatic shoreline detection by processing planview timex images using bi-LSTM Networks
| Τίτλος: | Automatic shoreline detection by processing planview timex images using bi-LSTM Networks |
|---|---|
| Συγγραφείς: | Marti-Puig, Pere, Serra-Serra, Moises, Ribas Prats, Francesca, Simarro Grande, Gonzalo, Caballería Suriñach, Miquel |
| Συνεισφορές: | Universitat Politècnica de Catalunya. Departament de Física, Universitat Politècnica de Catalunya. DF-GeoTech - Dinàmica de Fluids i Aplicacions Geofísiques i Tecnològiques |
| Έτος έκδοσης: | 2024 |
| Συλλογή: | Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
| Θεματικοί όροι: | Àrees temàtiques de la UPC::Enginyeria civil::Geologia, Coast changes, Image processing--Digital techniques, Coastal environment, Timex video images, Automatic shoreline detection, Bi-LSTM Neural Network, CIELAB colour space, Imatges--Processament--Tècniques digitals, Costes |
| Περιγραφή: | A new automatic shoreline detection method by using a bidirectional Long Short-Term Memory (bi-LSTM) Network that processes images column by column is presented. The model is trained on manually extracted shorelines from time-exposure video-images and is very robust against the selection of images for training. Thanks to the novelty of working with image columns, instead of with the whole image, the amount of labelled images for training is limited to a few tens or even less if the conditions are good. Moreover, this column approach makes the model to be robust to variable illuminated images and more easily interpretable, light and fast. There is a wide range of configuration parameters for the bi-LSTM layer by which the system works correctly, which facilitate to use the same network in different video stations. The highest accuracy is obtained by using CIELAB colour space. Without pre-processing the raw colour channels or defining a region of interest and without post-processing the obtained shorelines, the model demonstrates impressive accuracy with mean errors of 2.8 pixels (1.4 meters) in Castelldefels and 1.7 pixels (0.85 meters) in Barcelona.The method could also be effective for satellite shoreline detection by using as input channel the water index of the satellite detection techniques. ; This work has been funded by the Spanish government through the research project RTI2018-093941-B-C33 (MINECO/FEDER). ; Peer Reviewed ; Postprint (published version) |
| Τύπος εγγράφου: | article in journal/newspaper |
| Περιγραφή αρχείου: | 18 p.; application/pdf |
| Γλώσσα: | English |
| Relation: | https://www.sciencedirect.com/science/article/pii/S0957417423030683?ssrnid=4450721&dgcid=SSRN_redirect_SD; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093941-B-C33/ES/MORFODINAMICA DE PLAYAS PROTEGIDAS EN EL MEDITERRANEO FRENTE AL CAMBIO CLIMATICO: MODELADO/; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4450721&adobe_mc=MCMID%3D01557632360049780735594576724462562065%7CMCORGID%3D4D6368F454EC41940A4C98A6%2540AdobeOrg%7CTS%3D1711017047; http://hdl.handle.net/2117/405069 |
| DOI: | 10.1016/j.eswa.2023.122566 |
| Διαθεσιμότητα: | http://hdl.handle.net/2117/405069 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4450721&adobe_mc=MCMID%3D01557632360049780735594576724462562065%7CMCORGID%3D4D6368F454EC41940A4C98A6%2540AdobeOrg%7CTS%3D1711017047 https://doi.org/10.1016/j.eswa.2023.122566 |
| Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International ; http://creativecommons.org/licenses/by-nc-nd/4.0/ ; Open Access |
| Αριθμός Καταχώρησης: | edsbas.D18B2EE6 |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.1016/j.eswa.2023.122566 |
|---|