|Title:||Automatic identification approach for sea surface bubbles detection||Authors:||Fuertes, Juan José
Travieso, Carlos M.
Alonso, J. B.
|UNESCO Clasification:||3307 Tecnología electrónica||Keywords:||Information Systems Applications (incl.Internet), Computer Science, Database Management, Information Storage and Retrieval, Artificial Intelligence (incl. Robotics), Computation by Abstract Devices, Algorithm Analysis and Problem Complexity, Pattern Recognition, Sea Surface Image, Image Processing, Bubble Detection||Issue Date:||2011||Publisher:||0302-9743||Journal:||Lecture Notes in Computer Science||Conference:||6th International Conference on Hybrid Artificial Intelligence Systems (HAIS)
6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
6th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2011
|Abstract:||In this work a novel system for bubbles detection on sea surface images is presented. This application is basic 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: image pre-processing and enhancing in order to improve the bubbles features, and segmentation and bubbles detection. A combination system has been performed with Support Vector Machines (SVM) in order to detect the sea salinity, showing a recognition rate of 95.43%.||URI:||http://hdl.handle.net/10553/44049||ISBN:||9783642212185||ISSN:||0302-9743||DOI:||10.1007/978-3-642-21219-2_11||Source:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 6678 LNAI, p. 75-82|
|Appears in Collections:||Actas de congresos|