Please use this identifier to cite or link to this item:
https://doi.org/10.23919/ICCAS52745.2021.9649961
DC Field | Value | |
---|---|---|
dc.title | Sunlight Compensation for Vision Based Drone Detection | |
dc.contributor.author | Lau, YH | |
dc.contributor.author | Jun Liang, NS | |
dc.contributor.author | Seah, SX | |
dc.contributor.author | Srigrarom, S | |
dc.date.accessioned | 2022-03-25T06:53:07Z | |
dc.date.available | 2022-03-25T06:53:07Z | |
dc.date.issued | 2021-01-01 | |
dc.identifier.citation | Lau, YH, Jun Liang, NS, Seah, SX, Srigrarom, S (2021-01-01). Sunlight Compensation for Vision Based Drone Detection. 2021 21st International Conference on Control, Automation and Systems (ICCAS) 2021-October : 442-443. ScholarBank@NUS Repository. https://doi.org/10.23919/ICCAS52745.2021.9649961 | |
dc.identifier.isbn | 9788993215212 | |
dc.identifier.issn | 15987833 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/217717 | |
dc.description.abstract | Computer vision based object detection can be applied in security and monitoring scenarios, such as detecting and tracking drone intrusions using cameras. However, its effectiveness is dependent on environmental conditions. For example, under bright sunlight and clear sky conditions, the sunlight reflecting off a target could cause it to blend into the sky and prevent detection. In this paper, an algorithm to compensation for the effects of sunlight on object detection was proposed. The algorithm applied a localised contrast increase to the sky through RGB-HSV conversion and image extraction techniques, which avoided the generation of false positives among the treeline. Preliminary tests with prerecorded videos showed that the algorithm improves detection under bright sunlight conditions but the contrast gain had to be manually tuned. Methods to dynamically tune the gain, and field tests to determine the algorithm's real time effectiveness, are slated for future work. | |
dc.publisher | IEEE | |
dc.source | Elements | |
dc.type | Conference Paper | |
dc.date.updated | 2022-03-25T04:07:23Z | |
dc.contributor.department | TEMASEK LABORATORIES | |
dc.description.doi | 10.23919/ICCAS52745.2021.9649961 | |
dc.description.sourcetitle | 2021 21st International Conference on Control, Automation and Systems (ICCAS) | |
dc.description.volume | 2021-October | |
dc.description.page | 442-443 | |
dc.published.state | Published | |
Appears in Collections: | Staff Publications Elements |
Show simple item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
_ICCAS_2021__Sunlight_Compensation_for_Vision_Based_Drone_Detection.pdf | Published version | 3.97 MB | Adobe PDF | CLOSED | None |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.