Small-floating Target Detection in Sea Clutter via Visual Feature Classifying in the Time-Doppler Spectra
It is challenging to detect small-floating object in the sea clutter for a surface radar. In this paper, we have observed that the backscatters from the target brake the continuity of the underlying motion of the sea surface in the time-Doppler spectra (TDS) images. Following this visual clue, we exploit the local binary pattern (LBP) to measure the variations of texture in the TDS images. It is shown that the radar returns containing target and those only having clutter are separable in the feature space of LBP. An unsupervised one-class support vector machine (SVM) is then utilized to detect the deviation of the LBP histogram of the clutter. The outiler of the detector is classified as the target. In the real-life IPIX radar data sets, our visual feature based detector shows favorable detection rate compared to other three existing approaches.
Code (1)
Similar Papers 제목 키워드 기반
Visual Cue Integration for Small Target Motion Detection in Natural Cluttered Backgrounds
The robust detection of small targets against cluttered background is important for future artificial visual systems in searching and tracking applications. The insects' visual systems have demonstrated excellent ability…
Motion DetectionA Feedback Neural Network for Small Target Motion Detection in Cluttered Backgrounds
Small target motion detection is critical for insects to search for and track mates or prey which always appear as small dim speckles in the visual field. A class of specific neurons, called small target motion detectors…
Motion DetectionA Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds
Monitoring small objects against cluttered moving backgrounds is a huge challenge to future robotic vision systems. As a source of inspiration, insects are quite apt at searching for mates and tracking prey -- which alwa…
Motion DetectionBrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Models
Vision-language models (VLMs) achieve strong visual question answering (VQA) performance, but processing large cluttered images is computationally expensive when only a small region is relevant. Electroencephalography (E…
Visual Question AnsweringA Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds
Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the fly's visual system, a class of specific ne…