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7 May 2019 Challenges in object detection in above-water imagery
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Abstract
Many existing methods of object detection, including edge detection, blob detection, and background subtraction (implemented in libraries such as OpenCV) have proven to be enormously successful when applied to many types of video datasets. However, detecting objects over water presents challenges that are unique and not easily accommodated for by pre-existing algorithms available in popular image processing libraries. In this paper, existing approaches are brie y reviewed, and the challenges encountered in above-water video datasets are highlighted. A recently proposed approach to object detection in radar images - a novel, pixel-intensity statistic based thresholding approach | is then reviewed. In this paper, this approach has been successfully applied to EO/IR datasets as well, extending the implementation to ensure success when applied onto other types of image datasets.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sarah Babbitt, Tanya Gatsak, and Bhashyam Balaji "Challenges in object detection in above-water imagery", Proc. SPIE 11018, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII, 1101818 (7 May 2019); https://doi.org/10.1117/12.2518879
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