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Adaptive contour-based statistical background subtraction method for moving target detection in infrared video sequences |
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| Affiliation: | 1. Academy of Scientific and Innovative Research (AcSIR), New Delhi 110001, India;2. Computational Instrumentation, Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh 160030, India;3. Department of Computer Science and Engineering, Chitkara University, Himachal Pradesh, India;1. National Research Tomsk State University, 36 Lenin av., 634050 Tomsk, Russia;2. Rzhanov Institute of Semiconductor Physics of the Siberian Branch of the Russian Academy of Sciences, 13, akademika Lavrent’eva av., 630090 Novosibirsk, Russia;1. Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, Nanjing University of Information Science &Technology, Nanjing, 210044, China;2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, 210044, China;3. School of Physics and Optoelectronic Engineering, Nanjing University of Information Science &Technology, Nanjing, 210044, China;1. Nano-Optical Property Laboratory and Department of Physics, Kyung Hee University, Seoul 130-701, Republic of Korea;2. Department of Physics, North Carolina State University, Raleigh, NC 27695-8202, United States |
| Abstract: | A robust contour-based statistical background subtraction method for detection of non-uniform thermal targets in infrared imagery is presented. The foremost step of the method comprises of generation of background frame using statistical information of an initial set of frames not containing any targets. The generated background frame is made adaptive by continuously updating the background using the motion information of the scene. The background subtraction method followed by a clutter rejection stage ensure the detection of foreground objects. The next step comprises of detection of contours and distinguishing the target boundaries from the noisy background. This is achieved by using the Canny edge detector that extracts the contours followed by a k-means clustering approach to differentiate the object contour from the background contours. The post processing step comprises of morphological edge linking approach to close any broken contours and finally flood fill is performed to generate the silhouettes of moving targets. This method is validated on infrared video data consisting of a variety of moving targets. Experimental results demonstrate a high detection rate with minimal false alarms establishing the robustness of the proposed method. |
| Keywords: | Infrared Statistical background subtraction Contour saliency map Silhouettes |
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