scholarly journals Feature Extraction of Gear Fault Signal Based on Sobel Operator and WHT

2013 ◽  
Vol 20 (3) ◽  
pp. 551-559 ◽  
Author(s):  
Jian-Hua Cai ◽  
Wei-Wen Hu
Keyword(s):  
Feature Extraction ◽  
Edge Detection ◽  
Hough Transform ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Cross Term ◽  
Time Performance ◽  
Sobel Operator ◽  
Gear Fault ◽  
Influence Of Noise

Taking Wigner-Ville distribution of gear fault signal as a picture,Sobeloperator was applied for edge detection of picture and then Hough transform was used to extract signal feature. Some simulated and measured signals have been processed to demonstrate the effectiveness of new method, which was compared with traditional Wigner-Hough transform and SPWD-Hough transform. The results show that the proposed method can suppress cross term which is produced from using Wigner-Ville distribution to analyze multi-component signal, especially under the condition of low signal to noise ratio. The improved Wigner-Hough transform can effectively suppress the influence of noise and has a good real-time performance because its algorithm is fast. The proposed method provides an effective method to determine the state of gear accurately.

scholarly journals Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection

2021 ◽  
Vol 18 (5) ◽  
pp. 6771-6789
Author(s):  
Hongyan Xu ◽  
Keyword(s):  
Edge Detection ◽  
Digital Media ◽  
Copyright Protection ◽  
Detection Rate ◽  
Signal To Noise Ratio ◽  
Edge Computing ◽  
Absolute Difference ◽  
Watermark Image ◽  
Signal To Noise ◽  
Noise Ratio

<abstract> <p>With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.</p> </abstract>

Fluorescence Rejection in Raman Spectroscopy by Shifted-Spectra, Edge Detection, and FFT Filtering Techniques

1995 ◽  
Vol 49 (5) ◽  
pp. 630-638 ◽  
Author(s):  
P. A. Mosier-Boss ◽  
S. H. Lieberman ◽  
R. Newbery
Keyword(s):  
Raman Spectroscopy ◽  
Fourier Transform ◽  
Edge Detection ◽  
Fast Fourier Transform ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
First Derivative ◽  
Derivative Spectroscopy ◽  
Deconvolution Techniques ◽  
Filtering Techniques

The use of shifted-spectra, first-derivative spectroscopy (or edge detection), and fast Fourier transform filtering techniques for fluorescence rejection in Raman spectra is demonstrated. These techniques take advantage of the fact that Raman signals are very narrow in comparison to fluorescence bands in order to discriminate between the two. None of these techniques require modification of existing instrumentation. Fast Fourier transform filtering and deconvolution techniques also provide a means of improving spectral resolution and the signal-to-noise ratio.

Embedded Video System-Based Motion-Adaptive De-Interlacing Algorithm

2014 ◽  
Vol 1030-1032 ◽  
pp. 1696-1700
Author(s):  
Ying Li ◽  
Miao Nie ◽  
Rui Zhou
Keyword(s):  
Edge Detection ◽  
Motion Detection ◽  
Signal To Noise Ratio ◽  
Design Criterion ◽  
Vertical Resolution ◽  
Horizontal Edge ◽  
Virtual Image ◽  
Signal To Noise ◽  
Motion State ◽  
Insertion Algorithm

An modified motion-adaptive de-interlacing algorithm was proposed in view of defects of traditional motion-adaptive de-interlacing algorithm in the aspects of motion detection and adaptive interpolation.Bipolar consecutive four fields was exploited to design criterion of motion state which improved the accuracy of the motion detection.Field insertion algorithm was exploited for interpolation of the static region which could increase vertical resolution of the image.Traditional ELA algorithm was modified by multi-directional edge detection for the interpolation of the motion region which could increase the function of horizontal edge detection and enhance the level of consistency edge direction estimation.Experimental results show that the proposed de-interlacing algorithm improves Peak Signal-to-Noise Ratio (PSNR) and restrains the artifacts such as saw-tooth,interline flicker,motion virtual image.

scholarly journals Extracting low signal-to-noise ratio events with the Hough transform from sparse array data

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. WC43-WC51 ◽  
Author(s):  
Gil Averbuch ◽  
Jelle D. Assink ◽  
Pieter S. M. Smets ◽  
Läslo G. Evers
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Hough Transform ◽  
Signal To Noise Ratio ◽  
Automatic Detection ◽  
Image Processing Technique ◽  
Beam Forming ◽  
Signal To Noise ◽  
High Background ◽  
Noise Ratio

Low-frequency acoustic, i.e., infrasound, waves are measured by sparse arrays of microbarometers. Recorded data are processed by automatic detection algorithms based on array-processing techniques such as time-domain beam forming and [Formula: see text] analysis. These algorithms use a signal-to-noise ratio (S/N) value as a detection criterion. In the case of high background noise or in the presence of multiple coinciding signals, the event’s S/N decreases and can be missed by automatic processing. In seismology, detecting low-S/N events with geophone arrays is a well-known problem. Whether it is in global earthquake monitoring or reservoir microseismic activity characterization, detecting low-S/N events is needed to better understand the sources or the medium of propagation. We use an image-processing technique as a postprocessing step in the automatic detection of low S/N events. In particular, we consider the use of the Hough transform (HT) technique to detect straight lines in beam-forming results, i.e., a back azimuth (BA) time series. The presence of such lines, due to similar BA values, can be indicative of a low-S/N event. A statistical framework is developed for the HT parameterization, which includes defining a threshold value for detection as well as evaluating the false alarm rate. The method is tested on synthetic data and five years of recorded infrasound from glaciers. It is shown that the automatic detection capability is increased by detecting low-S/N events while keeping a low false-alarm rate.

Target Type Recognition Algorithm of Imaging GIF Fuze

2013 ◽  
Vol 416-417 ◽  
pp. 1170-1175
Author(s):  
Bin Liu ◽  
Yang Yu Fan ◽  
Jian Guo
Keyword(s):  
Feature Extraction ◽  
Image Segmentation ◽  
Edge Detection ◽  
Real Time ◽  
Target Recognition ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Target Type ◽  
Time Performance ◽  
Simulation Results

According to the requirement of aerial infrared target recognition, a group of image segmentation, edge detection, feature extraction, type recognition algorithms are put forward in this article after analysis and comparison of many algorithms. The simulation results show that the typical aerial target type recognition rate of this group of algorithms can reach more than 80%, so that the algorithms have higher ability of target type recognition, and its real-time performance can meet the requirement of imaging GIF fuze.

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