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Sensors 2017, 17(3), 659; doi:10.3390/s17030659

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

1
Telecommunications Technology Association, 47 Bundang-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 13591, Korea
2
School of Electronics and Information Engineering, Korea Aerospace University, 76 Hanggongdaehak-ro Deogyang-gu, Goyang-si, Gyeonggi-do 10540, Korea
3
Satrec Initiative, 21 Yuseong-daero 1628beon-gil Yuseong-gu, Daejeon 34054, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Joonki Paik
Received: 10 January 2017 / Revised: 6 March 2017 / Accepted: 18 March 2017 / Published: 22 March 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [19818 KB, uploaded 22 March 2017]   |  

Abstract

Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos. View Full-Text
Keywords: video surveillance; video analytics; shadow detection; shadow removal; object extraction; regions of light sources; nighttime video; vertical histogram video surveillance; video analytics; shadow detection; shadow removal; object extraction; regions of light sources; nighttime video; vertical histogram
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lee, G.-B.; Lee, M.-J.; Lee, W.-K.; Park, J.-H.; Kim, T.-H. Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video. Sensors 2017, 17, 659.

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