An active contour algorithm for spectrogram track detection
This paper proposes an active contour framework for spectrogram track detection. A potential energy is proposed which results in feature extraction at a signal-to-noise ratio (SNR) of 0.5dB. We show, through complexity analysis, that this is achievable in real-time.
active contour spectrogram periodic time series remote sensing low signal-to-noise ratio statistical pattern recognition