Plant Leaf Imaging using Time of Flight Camera under Sunlight, Shadow and Room Conditions

Wajahat Kazmi, Sergi Foix, Guillem Alenya

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

12 Citationer (Scopus)
688 Downloads (Pure)

Abstrakt

In this article, we analyze the effects of ambient light on Time of Flight (ToF) depth imaging for a plant's leaf in sunlight, shadow and room conditions. ToF imaging is sensitive to ambient light and we try to find the best possible integration times (IT) for each condition. This is important in order to optimize the camera calibration. Our analysis is based on several statistical metrics estimated from the ToF data. We explain the estimation of the metrics and propose a method of predicting the deteriorating behavior of the data in each condition using camera flags. Finally, we also propose a method to improve the quality of a ToF image taken in a mixed condition having different ambient light exposures.
OriginalsprogEngelsk
TitelIEEE International Symposium on Robotic and Sensors Environments
Antal sider6
ForlagIEEE Computer Society Press
Publikationsdatonov. 2012
Sider192-197
ISBN (Trykt)978-1-4673-2705-3
DOI
StatusUdgivet - nov. 2012
Begivenhed2012 IEEE International Symposium on Robotic and Sensors Environments (ROSE 2012) - Magdeburg, Tyskland
Varighed: 16 nov. 201218 nov. 2012

Konference

Konference2012 IEEE International Symposium on Robotic and Sensors Environments (ROSE 2012)
LandTyskland
ByMagdeburg
Periode16/11/201218/11/2012

Fingeraftryk Dyk ned i forskningsemnerne om 'Plant Leaf Imaging using Time of Flight Camera under Sunlight, Shadow and Room Conditions'. Sammen danner de et unikt fingeraftryk.

  • Citationsformater

    Kazmi, W., Foix, S., & Alenya, G. (2012). Plant Leaf Imaging using Time of Flight Camera under Sunlight, Shadow and Room Conditions. I IEEE International Symposium on Robotic and Sensors Environments (s. 192-197). IEEE Computer Society Press. https://doi.org/10.1109/ROSE.2012.6402615