Abstract
The presence of atmospheric turbulence over horizontal imaging paths introduces time-varying perturbations and blur in the scene that severely degrade the performance of moving object detection and tracking systems of vision applications. This paper proposed a simple and efficient algorithm for moving target detection under turbulent media, based on adaptive background subtraction approach with different types of background models followed by adaptive global thresholding to detect foreground. This proposed method is implemented in MATLAB and tested on turbulence degraded video sequences. Further, this proposed method is also compared with state-of-the-art method published in the literature. The result shows that the detection performance by proposed algorithm is better. Further, the proposed method can be easily implemented in FPGA-based hardware.
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Veenu, C., Ajay, K., Anurekha, S. (2018). Moving Target Detection Under Turbulence Degraded Visible and Infrared Image Sequences. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 703. Springer, Singapore. https://doi.org/10.1007/978-981-10-7895-8_1
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DOI: https://doi.org/10.1007/978-981-10-7895-8_1
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