Title :
A machine vision based method for atmospheric circulation classification
Author :
Zagouras, A. ; Argiriou, A.A. ; Flocas, H.A. ; Economou, George ; Fotopoulos, Spiros
Author_Institution :
Dept. of Phys., Univ. of Patras, Patras, Greece
Abstract :
Weather maps refer to meteorological data that characterize the atmospheric circulation in a region. The classification of weather maps into categories becomes an important task for understanding regional climate. Towards this goal, manual and semiautomatic techniques have been used, requiring manpower and supervision. In this paper, we propose a machine vision based method for the classification of weather maps into distinct classes. The chain code descriptor is applied to extract the feature of isobaric lines and we introduce the double-side chain code (DSCC) histogram for feature representation. Handling DSCC histograms as multidimensional vectors, the k-nearest neighbors (k-NN) algorithm classifies the objects to an appropriate number of classes, based on closest training set in the feature space. This method provides an automated and more dasiaobjectivepsila classification scheme, applying straightforward to the input weather map´s image.
Keywords :
atmospheric movements; atmospheric pressure; atmospheric techniques; cartography; climatology; computer vision; feature extraction; geophysical signal processing; image classification; image coding; image representation; object detection; weather forecasting; DSCC histogram; atmospheric circulation classification scheme; closest training set; double-side chain code histogram descriptor; feature extraction; feature representation; isobaric line; k-nearest neighbor classification algorithm; machine vision-based method; meteorological data; multidimensional vector; object classification; regional climate; semiautomatic technique; weather map image classification; Feature extraction; Histograms; Image databases; Isobaric; Laboratories; Machine vision; Meteorology; Physics; Spatial databases; Weather forecasting; chain code; k- nearest neighbors algorithm; machine vision; synoptic climatology;
Conference_Titel :
Digital Signal Processing, 2009 16th International Conference on
Conference_Location :
Santorini-Hellas
Print_ISBN :
978-1-4244-3297-4
Electronic_ISBN :
978-1-4244-3298-1
DOI :
10.1109/ICDSP.2009.5201149