A fast mathematical morphology filter on one dimensional sampled signal

• Published in: 2017 International Conference on Control, Automation and Information Sciences (ICCAIS) pp. 233 - 238
• Main Authors: Yongxin Chou, Benlian Xu, Ya Gu, Ruilei Zhang, Liguo Wang, Yi Jin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2017
• Subjects: Filtering theory; Information filters; Mathematical model; mathematical morphology filters; Morphology; one dimensional signal; Pulse measurements; real-time; sliding window
• ISSN: 2475-7896
• DOI: 10.1109/ICCAIS.2017.8217582

As a kind of common digital signal processing methods, mathematical morphology filter (MMF) has been employed to process the one dimensional sampled signals. However, because of the heavy time-consumption, it is difficult to use this method in data acquisition and processing system. Therefore, an improved MMF is proposed in this study on the basis of MMF and the process of data updating during one dimensional signal sampling. The buffer in data acquisition system is as a "window" sliding in data, and the sliding window iterative theory is engaged in improving the MMF and reducing its time-consumption. A simulated signal and some pulse signals are as the experimental data to verify the proposed method and the MMF. The results show that the proposed method has less time-consumption and keeps the filtering accuracy in the meantime, and could be used to process one dimensional signal in real-time.