Title :
Object counting in high resolution remote sensing images with OTB
Author :
Christophe, E. ; Inglada, J.
Author_Institution :
CRISP, Singapore, Singapore
Abstract :
Satellite observation is particularly enticing due to its large acquisition capabilities. However these large capabilities kindle new challenges for information analysis. Object counting is one of those. To help releasing constraints on the human operator, it is important to free him from repetitive tasks and focus his attention on the high level tasks for which algorithms are not suitable yet. This abstract focuses on building counting in dense areas. The processing is done using the Or-feo Toolbox, an open-source image processing library. This paper proposes several methods with different trade-offs in terms of performance and user involvement. The method has been adapted and successfully used in other situations, as for instance counting tree stands or tents in a refugee camp.
Keywords :
geophysical image processing; image resolution; information analysis; object recognition; remote sensing; Orfeo toolbox; building counting; high resolution remote sensing images; human operator; information analysis; object counting; open source image processing library; otb; refugee camp; repetitive tasks; satellite observation; tents; tree stands; Consumer electronics; Humans; Image processing; Image resolution; Information analysis; Libraries; Object recognition; Open source software; Remote sensing; Satellites; High Resolution Remote Sensing; Object Counting; Object Recognition;
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.2009.5417482