Statella, ThiagoPina, PedroSilva, Erivaldo Antonio da [UNESP]2014-05-272014-05-272011-11-28Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7042 LNCS, p. 533-540.0302-97431611-3349http://hdl.handle.net/11449/72815This paper presents three methods for automatic detection of dust devils tracks in images of Mars. The methods are mainly based on Mathematical Morphology and results of their performance are analyzed and compared. A dataset of 21 images from the surface of Mars representative of the diversity of those track features were considered for developing, testing and evaluating our methods, confronting their outputs with ground truth images made manually. Methods 1 and 3, based on closing top-hat and path closing top-hat, respectively, showed similar mean accuracies around 90% but the time of processing was much greater for method 1 than for method 3. Method 2, based on radial closing, was the fastest but showed worse mean accuracy. Thus, this was the tiebreak factor. © 2011 Springer-Verlag.533-540engDust Devils TracksFeature DetectionMarsMathematical MorphologyAutomatic DetectionAutomatic methodData setsDust devilsFeature detectionGround truthMartian dustSurface of MarsTime of processingComputer visionDustStatistical testsSurface testingMathematical morphologyTrabalho apresentado em evento10.1007/978-3-642-25085-9_63Acesso aberto2-s2.0-8185517712791035450045071350000-0002-7069-0479