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Open AccessArticle

Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images

1
Agency for Defense Development, P.O. Box 35, Yuseong, Daejeon 34186, Korea
2
Department of Electronic Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan, Gyeongbuk 38541, Korea
3
Department of Electrical Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(4), 996; https://doi.org/10.3390/s18040996
Received: 1 February 2018 / Revised: 24 March 2018 / Accepted: 25 March 2018 / Published: 27 March 2018
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
This paper proposes the automatic coast mode tracking of centroid trackers for infrared images to overcome the target occlusion status. The centroid tracking method, using only the brightness information of an image, is still widely used in infrared imaging tracking systems because it is difficult to extract meaningful features from infrared images. However, centroid trackers are likely to lose the track because they are highly vulnerable to screened status by the clutter or background. Coast mode, one of the tracking modes, maintains the servo slew rate with the tracking rate right before the loss of track. The proposed automatic coast mode tracking method makes decisions regarding entering coast mode by the prediction of target occlusion and tries to re-lock the target and resume the tracking after blind time. This algorithm comprises three steps. The first step is the prediction process of the occlusion by checking both matters which have target-likelihood brightness and which may screen the target despite different brightness. The second step is the process making inertial tracking commands to the servo. The last step is the process of re-locking a target based on the target modeling of histogram ratio. The effectiveness of the proposed algorithm is addressed by presenting experimental results based on computer simulation with various test imagery sequences compared to published tracking algorithms. The proposed algorithm is tested under a real environment with a naval electro-optical tracking system (EOTS) and airborne EO/IR system. View Full-Text
Keywords: infrared image; automatic tracking; electro-optical tracking system; coast mode tracking infrared image; automatic tracking; electro-optical tracking system; coast mode tracking
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MDPI and ACS Style

Kim, S.; Jang, G.-I.; Kim, S.; Kim, J. Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images. Sensors 2018, 18, 996. https://doi.org/10.3390/s18040996

AMA Style

Kim S, Jang G-I, Kim S, Kim J. Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images. Sensors. 2018; 18(4):996. https://doi.org/10.3390/s18040996

Chicago/Turabian Style

Kim, Sohyun; Jang, Gwang-Il; Kim, Sungho; Kim, Junmo. 2018. "Computationally Efficient Automatic Coast Mode Target Tracking Based on Occlusion Awareness in Infrared Images" Sensors 18, no. 4: 996. https://doi.org/10.3390/s18040996

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