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Sunlight Compensation for Vision Based Drone Detection |
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Yan Han Lau, Niven Jun Liang Sie, Shao Xuan Seah, Sutthiphong Srigrarom(National University of Singapore, Singapore) |
| 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. 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. |
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