POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING
Honey bees have crucial role in pollination across the world. This paper presents a simple, non-invasive, system for pollen bearing honey bee detection in surveillance video obtained at the entrance of a hive. The proposed system can be used as a part of a more complex system for tracking and counti...
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-5ae21452d4804c6ba605b66df3c0426c2020-11-25T01:30:46ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502016-06-01III-7515710.5194/isprs-annals-III-7-51-2016POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORINGZ. Babic0R. Pilipovic1V. Risojevic2G. Mirjanic3Faculty of Electrical Engineering, University of Banja Luka, Banja Luka, Bosnia and HerzegovinaFaculty of Electrical Engineering, University of Banja Luka, Banja Luka, Bosnia and HerzegovinaFaculty of Electrical Engineering, University of Banja Luka, Banja Luka, Bosnia and HerzegovinaFaculty of Agriculture, University of Banja Luka, Banja Luka, Bosnia and HerzegovinaHoney bees have crucial role in pollination across the world. This paper presents a simple, non-invasive, system for pollen bearing honey bee detection in surveillance video obtained at the entrance of a hive. The proposed system can be used as a part of a more complex system for tracking and counting of honey bees with remote pollination monitoring as a final goal. The proposed method is executed in real time on embedded systems co-located with a hive. Background subtraction, color segmentation and morphology methods are used for segmentation of honey bees. Classification in two classes, pollen bearing honey bees and honey bees that do not have pollen load, is performed using nearest mean classifier, with a simple descriptor consisting of color variance and eccentricity features. On in-house data set we achieved correct classification rate of 88.7% with 50 training images per class. We show that the obtained classification results are not far behind from the results of state-of-the-art image classification methods. That favors the proposed method, particularly having in mind that real time video transmission to remote high performance computing workstation is still an issue, and transfer of obtained parameters of pollination process is much easier.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-7/51/2016/isprs-annals-III-7-51-2016.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Z. Babic R. Pilipovic V. Risojevic G. Mirjanic |
spellingShingle |
Z. Babic R. Pilipovic V. Risojevic G. Mirjanic POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
Z. Babic R. Pilipovic V. Risojevic G. Mirjanic |
author_sort |
Z. Babic |
title |
POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING |
title_short |
POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING |
title_full |
POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING |
title_fullStr |
POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING |
title_full_unstemmed |
POLLEN BEARING HONEY BEE DETECTION IN HIVE ENTRANCE VIDEO RECORDED BY REMOTE EMBEDDED SYSTEM FOR POLLINATION MONITORING |
title_sort |
pollen bearing honey bee detection in hive entrance video recorded by remote embedded system for pollination monitoring |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2016-06-01 |
description |
Honey bees have crucial role in pollination across the world. This paper presents a simple, non-invasive, system for pollen bearing
honey bee detection in surveillance video obtained at the entrance of a hive. The proposed system can be used as a part of a more
complex system for tracking and counting of honey bees with remote pollination monitoring as a final goal. The proposed method is
executed in real time on embedded systems co-located with a hive. Background subtraction, color segmentation and morphology
methods are used for segmentation of honey bees. Classification in two classes, pollen bearing honey bees and honey bees that do
not have pollen load, is performed using nearest mean classifier, with a simple descriptor consisting of color variance and
eccentricity features. On in-house data set we achieved correct classification rate of 88.7% with 50 training images per class. We
show that the obtained classification results are not far behind from the results of state-of-the-art image classification methods. That
favors the proposed method, particularly having in mind that real time video transmission to remote high performance computing
workstation is still an issue, and transfer of obtained parameters of pollination process is much easier. |
url |
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-7/51/2016/isprs-annals-III-7-51-2016.pdf |
work_keys_str_mv |
AT zbabic pollenbearinghoneybeedetectioninhiveentrancevideorecordedbyremoteembeddedsystemforpollinationmonitoring AT rpilipovic pollenbearinghoneybeedetectioninhiveentrancevideorecordedbyremoteembeddedsystemforpollinationmonitoring AT vrisojevic pollenbearinghoneybeedetectioninhiveentrancevideorecordedbyremoteembeddedsystemforpollinationmonitoring AT gmirjanic pollenbearinghoneybeedetectioninhiveentrancevideorecordedbyremoteembeddedsystemforpollinationmonitoring |
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