Morphological filtering of noisy images

1990 ◽  
Author(s):  
Lasse Koskinen ◽  
Jaakko T. Astola ◽  
Yrjo A. Neuvo
Keyword(s):  
Noisy Images ◽  
Morphological Filtering

scholarly journals Soft morphological filtering using hypergraphs

2021 ◽  
Vol 1085 (1) ◽  
pp. 012038
Author(s):  
Nuja M Unnikrishnan ◽  
Mini Tom ◽  
V Bino Sebastian ◽  
K V Thomas
Keyword(s):  
Morphological Filtering

scholarly journals Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 52
Author(s):  
Tongtong Liu ◽  
Lingli Cui ◽  
Chao Zhang
Keyword(s):  
Frequency Conversion ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Operating Efficiency ◽  
Planetary Gearbox ◽  
Noise Interference ◽  
Multi Scale ◽  
Morphological Filtering ◽  
Diagnosis Method ◽  
Simulation Signal

The turn domain resampling (TDR) method is proposed in the paper on the basis of the existing angle domain resampling for solving the problem of non-fixed fault frequency under variable working conditions. TDR can select the appropriate sampling order according to the influence of frequency conversion, which avoided the error caused by the spline interpolation method. It can provide accurate parameters for the subsequent calculation of the equivalent frequency order. Variable multi-scale morphological filtering (VMSMF) method is proposed for the purpose of further reducing the interference of noise in resampling signal to feature extraction. VMSMF adaptively selects structural elements according to the parameter change of impact signal to make its scale more targeted. It only needs to calculate once using the optimal structural unit for a particular impact, and the filtering accuracy and operating efficiency have been greatly improved. The main steps of this article are as follows. First, the TDR is used to resample the original signal as to get the resampling signal which is still submerged by the strong noise. In the second step, VMSMF is used to filter the resampling signal to obtain the signal with less noise interference. Finally, the fault characteristics of the filtering signal was extracted and compared with the possible fault frequency calculated by the sampling parameters provided by resampling, so as to determine the fault type of the planetary gearbox. By analyzing the simulation signal and the experimental signal respectively, this method can find out the corresponding fault characteristics effectively.

A performance enhanced time-varying morphological filtering method for bearing fault diagnosis

Measurement ◽  
2021 ◽  
Vol 176 ◽  
pp. 109163
Author(s):  
Bingyan Chen ◽  
Dongli Song ◽  
Weihua Zhang ◽  
Yao Cheng ◽  
Zhiwei Wang
Keyword(s):  
Fault Diagnosis ◽  
Time Varying ◽  
Filtering Method ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Morphological Filtering ◽  
A Performance

Rectification-adapted snake for complex-boundary segmentation in noisy images

2013 ◽  
Author(s):  
Din-Yuen Chan ◽  
Roy C. Hsu ◽  
Pang-Hao Wu ◽  
Cheng-Ting Liu
Keyword(s):  
Noisy Images ◽  
Complex Boundary
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