Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/44058
| Título: | Bubbles detection on sea surface images | Autores/as: | Travieso, Carlos M. Ferrer, Miguel A. Alonso, Jesús B. |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Support Vector Machine , Recognition Rate , European Space Agency , Logic Combination , Practical Salinity Unit | Fecha de publicación: | 2010 | Editor/a: | 0302-9743 | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | 20th International Conference on Artificial Neural Networks | Resumen: | In this work a novel system for sea surface images pre-processing and processing has been developed in order to detect bubbles on the sea surface. This application is fundamental to verify radiometer satellite systems which are used to the study of the floor humidity and the sea salinity. 160 images of 8 kinds of salinity have been processed, 20 per class. Two main steps have been implemented; the first step is the image pre-processing and enhancing, in order to improve the bubbles detection. The second step is the segmentation and the bubbles detection. A combination system has been used in order to improve the final result, getting a recognition rate of 95.43%. | URI: | http://hdl.handle.net/10553/44058 | ISBN: | 978-3-642-15818-6 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-642-15819-3_73 | Fuente: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 6352 LNCS, p. 565-568 |
| Colección: | Actas de congresos |
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