Title :
Parameter-free clustering: Application to fawns detection
Author :
Cerra, Daniele ; Israel, Martin ; Datcu, Mihai
Author_Institution :
German Aerosp. Center, Remote Sensing Technol. Inst., Wessling, Germany
Abstract :
Many fawns and other wild animals are killed by mowing machines every year. To prevent them from being killed or injured, a sensor system is being developed to detect the fawns hidden in meadows under mowing. Beside a microwave radar system, two cameras (thermal infrared and RGB) take a picture at the mower´s current location. This contribution focuses on the compression-based algorithm that will be adopted to detect the locations containing a fawn hiding in the grass: such approach, being parameter-free, allows performing a fully unsupervised clustering by exploiting the intrinsic properties of data compression to estimate the amount of shared information between two images.
Keywords :
geophysical image processing; image recognition; image segmentation; infrared imaging; pattern clustering; remote sensing by radar; RGB camera; compression-based algorithm; fawns detection; image analysis; microwave radar system; mowing machines; parameter-free clustering; pattern recognition; sensor system; thermal infrared camera; wild animals; Animals; Cameras; Clustering algorithms; Data compression; Image analysis; Image coding; Infrared detectors; Infrared image sensors; Radar detection; Sensor systems; Parameter free; image analysis; pattern recognition; similarity measure;
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Electronic_ISBN :
978-1-4244-3395-7
DOI :
10.1109/IGARSS.2009.5418293