Signal Feature Recognition in Time-Frequency Domain Using Edge Detection Algorithms (CROSBI ID 683143)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Milanović, Željka ; Saulig, Nicoletta ; Marasović, Ivan
engleski
Signal Feature Recognition in Time-Frequency Domain Using Edge Detection Algorithms
We propose an approach to discern components in multicomponent, stationary and nonstationary signals by application of edge detection techniques to the time-frequency (TF) plane. The approach is based upon the use of a robust to noise computer vision edge detection algorithms, which can be used to precisely mark the position of the component in the TF plane independent of its time or frequency support. The results show the proposed method correctly detects positions of stationary signals with low error even in signals heavily corrupted by Additive White Gaussian Noise (AWGN) and other color noise environments, tested for Signal-to-Noise Ratio (SNR) of 0dB and 6dB. Positions of stationary components in the TF plane are detected with error of 2\% and nonstationary with error of 6%. Results with synthetic signals and a real-life signal (bat-echolocation) indicate that the method can be used in identifying components in noisy environments using a computationally less costly method that outperforms previously proposed methods by offering faster computational speed and smaller processor workload.
Computer vision ; edge detection ; Image segmentation ; Time-frequency domain ; denoising ; nonstationary signals
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Podaci o prilogu
1
2019.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 4th International Conference on Smart and Sustainable Technologies (SpliTech 2019)
Perković, Toni ; Vukojević, Katarina ; Rodrigues, Joel ; Nižetić, Sandro ; Patrono, Luigi ; Šolić, Petar
Piscataway (NJ): Institute of Electrical and Electronics Engineers (IEEE)
978-953-290-091-0
Podaci o skupu
4th International Conference on Smart and Sustainable Technologies (SpliTech)
predavanje
18.06.2019-21.06.2019
Bol, Hrvatska; Split, Hrvatska