Research on Defect Images Fusion Method Based on Regional Energy Similarity

2013 ◽  
Vol 791-793 ◽  
pp. 1957-1960
Author(s):  
Yu Lan Wei ◽  
Bing Li ◽  
Ying Ying Fan
Keyword(s):  
Single Point ◽  
Engineering Application ◽  
Low Frequency ◽  
Fusion Rule ◽  
Experimental Result ◽  
It Use ◽  
Wavelet Method ◽  
Regional Energy ◽  
Local Areas ◽  
Energy Similarity

Because the fusion rules which are based on coefficient of a single point and coefficient of region has one-sidedness and are easy to make blending images lack fidelity, a new fusion rule is put forward. When this fusion rule fuses the low frequency sub-band resolved by wavelet method, it adequately consider the local areas regional energy and the regional energys similarity of the image which is need to fuse, and it use threshold to choose appropriate fusion rule. Experimental result indicated that this way can preferably keep detail features of the image, and it has some engineering application value.

scholarly journals Combining Regional Energy and Intuitionistic Fuzzy Sets for Infrared and Visible Image Fusion

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7813
Author(s):  
Xiaoxue Xing ◽  
Cong Luo ◽  
Jian Zhou ◽  
Minghan Yan ◽  
Cheng Liu ◽  
...  
Keyword(s):  
Fuzzy Sets ◽  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Intuitionistic Fuzzy Sets ◽  
Target Information ◽  
Fusion Image ◽  
Visible Image ◽  
Regional Energy ◽  
Intuitionistic Fuzzy

To get more obvious target information and more texture features, a new fusion method for the infrared (IR) and visible (VIS) images combining regional energy (RE) and intuitionistic fuzzy sets (IFS) is proposed, and this method can be described by several steps as follows. Firstly, the IR and VIS images are decomposed into low- and high-frequency sub-bands by non-subsampled shearlet transform (NSST). Secondly, RE-based fusion rule is used to obtain the low-frequency pre-fusion image, which allows the important target information preserved in the resulting image. Based on the pre-fusion image, the IFS-based fusion rule is introduced to achieve the final low-frequency image, which enables more important texture information transferred to the resulting image. Thirdly, the ‘max-absolute’ fusion rule is adopted to fuse high-frequency sub-bands. Finally, the fused image is reconstructed by inverse NSST. The TNO and RoadScene datasets are used to evaluate the proposed method. The simulation results demonstrate that the fused images of the proposed method have more obvious targets, higher contrast, more plentiful detailed information, and local features. Qualitative and quantitative analysis results show that the presented method is superior to the other nine advanced fusion methods.

A Novel Broadband Vibration Energy Harvester

2014 ◽  
Vol 644-650 ◽  
pp. 3560-3563
Author(s):  
Yu Liu ◽  
Xiao Yan He ◽  
Shen Liu ◽  
Ying Wu ◽  
Yi Ou
Keyword(s):  
Resonance Frequency ◽  
Energy Harvester ◽  
Engineering Application ◽  
Low Frequency ◽  
Structure Design ◽  
Vibration Energy ◽  
Vibration Energy Harvester ◽  
Collector Efficiency ◽  
Energy Acquisition ◽  
Mode Energy

A single resonance frequency is the main factor of limiting vibration energy collector efficiency. In this paper, the multi degree of freedom oscillation adjusting bandwidth scheme is reported, designing a kind of new broadband vibration energy harvester, which has multi-mode energy acquisition, multi freedom vibration and broadband characteristics. Firstly, Broadband energy collector structure design. Secondly, Combining with the main vibration form, using the ANSYS carried out a detailed analysis of its working model. Finally, designing the prototype and doing some experimental verification, the results show that the designed energy collector with low frequency and wideband energy acquisition performance, the frequency domain of energy collection is 57.6 to 69.45HZ ,which break through the bottleneck of traditional single resonance frequency of energy acquisition, has a high value of theory and engineering application.

Principle and Simulation Study on Multi Point-Single Point Incremental Combined Forming for Sheet Metal

2009 ◽  
Vol 626-627 ◽  
pp. 273-278 ◽  
Author(s):  
X.J. Li ◽  
Ming Zhe Li ◽  
C.G. Liu ◽  
Zhong Yr Cai
Keyword(s):  
Sheet Metal ◽  
Single Point ◽  
Experimental Result ◽  
Work Piece ◽  
The Novel ◽  
Forming Process ◽  
Explicit Finite Element ◽  
Forming Defect ◽  
Forming Technology ◽  
Elastic Cushion

Based on Multi-Point (MP) forming technology and Single-Point Incremental (SPI) forming technology, MP-SPI combined forming method for sheet metal is proposed, the principle and two different forming techniques are illustrated firstly. Then the paper is focused on numerical analysis for the novel forming technique with explicit Finite Element (FE) algorithm. During simulation of spherical work-piece, dimpling occurs as a main forming defect in MP-SPI combined forming process. Simulation results show that the dimpling defect can be suppressed effectively by using elastic cushion. An appropriate thickness of elastic cushion is necessary to prevent dimpling. And also the deformation of the work-piece is sensitive to the shape of elastic cushion. The combined forming test shows that the numerical simulation result is closed to the experimental result.

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Recognition Rate ◽  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
License Plate Recognition ◽  
Image Pixels

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

Use of seismoscope records to determine ML and peak velocities

1984 ◽  
Vol 74 (1) ◽  
pp. 315-324
Author(s):  
David M. Boore
Keyword(s):  
Lower Bound ◽  
San Francisco ◽  
Peak Velocity ◽  
Response Spectrum ◽  
Single Point ◽  
Empirical Relation ◽  
Low Frequency ◽  
Simulation Method ◽  
Horizontal Velocity ◽  
Earthquake Moment

Abstract More information about ground motion can be extracted from seismoscope records than a single point on a response spectrum. To demonstrate this, the relation between seismoscope response and Wood-Anderson instrument output and peak horizontal ground velocity has been studied by simulating the various responses for a range of distances and magnitudes. The simulations show that the relation used by Jennings and Kanamori (1979) to convert from peak seismoscope readings to the peak response of a Wood-Anderson instrument has a distance- and magnitude-dependent systematic error. The error is negligible, however, for modern seismoscopes at distances of a few tens of kilometers. At several hundred kilometers, the relation underestimates the Wood-Anderson response by as much as a factor of two. The spread in Jennings and Kanamori's estimate of ML for the 1906 San Francisco earthquake, recorded on seismoscopes having relatively low natural frequencies (0.26 and 0.5 Hz), is reduced by the results in this paper—the upper value, from a seismoscope in Carson City, Nevada, at 290 km from the fault, going from ML = 7.2 to ML = 7.0 and the lower value, from Yountville, California (R ≈ 60 km), going from about 6.3 to 6.4. About 0.3 units of the remaining spread may be due to local geologic site conditions. If the 0.3 units is distributed equally between the Yountville and Carson City recordings, the estimates of ML for the San Francisco earthquake then become 6.5 and 6.8, somewhat lower than Jennings and Kanamori's final estimates of 634 to 7. Although the error in using the relation of Jennings and Kanamori to estimate Wood-Anderson response was at most a factor of 1.6 for the 1906 earthquake, the error can be substantially larger for smaller earthquakes recorded on similar low frequency seismoscopes. The relation between Wood-Anderson and seismoscope response used by Jennings and Kanamori can be combined with an empirical relation between peak horizontal velocity and Wood-Anderson response to predict peak velocity from seismocope recordings. The simulations show that this relation (vmax = 8.1Awa, where vmax is the peak horizontal velocity in centimeters/second and Awa is one-half the range of the Wood-Anderson motion in meters) forms a lower bound for estimates of peak velocity from seismoscope recordings. The relation is good for stations within about 100 km of earthquakes with moment magnitudes of about 4.5 to 6.5, and it underestimates peak velocity by factors up to 2 or 3 for larger earthquakes at distances within 100 km. An application of the simulation method to the 1976 Guatemala earthquake (moment magnitude = 7.6) results in 37 cm/sec as a lower bound to vmax, with 66 cm/sec as a more likely value, from the seismocope recording in Guatemala City (approximately 25 km from the Motagua fault).

scholarly journals Pansharpening with a Gradient Domain GIF Based on NSST

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 229
Author(s):  
Jiao Jiao ◽  
Lingda Wu
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Objective Evaluation ◽  
Data Sets ◽  
Multi Scale ◽  
Guided Image Filter ◽  
Gradient Domain ◽  
Spatial Quality

In order to improve the fusion quality of multispectral (MS) and panchromatic (PAN) images, a pansharpening method with a gradient domain guided image filter (GIF) that is based on non-subsampled shearlet transform (NSST) is proposed. First, multi-scale decomposition of MS and PAN images is performed by NSST. Second, different fusion rules are designed for high- and low-frequency coefficients. A fusion rule that is based on morphological filter-based intensity modulation (MFIM) technology is proposed for the low-frequency coefficients, and the edge refinement is carried out based on a gradient domain GIF to obtain the fused low-frequency coefficients. For the high-frequency coefficients, a fusion rule based on an improved pulse coupled neural network (PCNN) is adopted. The gradient domain GIF optimizes the firing map of the PCNN model, and then the fusion decision map is calculated to guide the fusion of the high-frequency coefficients. Finally, the fused high- and low-frequency coefficients are reconstructed with inverse NSST to obtain the fusion image. The proposed method was tested using the WorldView-2 and QuickBird data sets; the subjective visual effects and objective evaluation demonstrate that the proposed method is superior to the state-of-the-art pansharpening methods, and it can efficiently improve the spatial quality and spectral maintenance.

A Automatic Vehicle License Plate Location Based on Sobel Edge Method

2013 ◽  
Vol 479-480 ◽  
pp. 911-915
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
Edge Image ◽  
License Plate Location ◽  
Scan Time ◽  
Plate Location ◽  
Feature Values ◽  
Edge Method

This thesis is to approach license-plate location using Sobel mask operator for license-plate location. This thesis consists of three main parts. The first part is to gray and HSI transform and cut image to reduce image scan time. The second part is to use Sobel edge function and use scan line scanning image to find license-plate. The third part is to locate and extract the license-plate. The last step is license plate and through 2D Haar Discrete Wavelet Transform two times, after transform only selected LL low-frequency parts and will the data arrange into a row when license plate the feature values. The experimental result can be high location rate. Hence, Sobel edge image is a good each of methods.

Wavelet Method to Extract Shock Signal of Debris Flow

2011 ◽  
Vol 199-200 ◽  
pp. 958-965
Author(s):  
Hong Kai Chen ◽  
Hong Mei Tang ◽  
Yu Ping Zhang ◽  
Xiao Ying He
Keyword(s):  
Debris Flow ◽  
Energy Distribution ◽  
Model Experiment ◽  
Low Frequency ◽  
Wavelet Method ◽  
Design Load ◽  
Shock Energy ◽  
Initial Shock ◽  
Debris Flow Disaster

The shock signal’s fluctuation characteristics of debris flow stem from two aspects, one is the composition of debris flow with the solid and the liquid, another is the surging property of debris flow in motion. Based on the initial shock signals collected in model experiment in laboratory, 9 shock spectrum levels are decomposed by the db8 wavelet method, i.e., 0~0.195Hz, 0.195~ 0.391Hz, 0.391~0.781Hz, 0.781~1.5625Hz, 1.563~3.125Hz, 3.125~ 6.25Hz, 6.25~12.5 Hz, 12.5~25Hz, and 25~50Hz. Taking the peak each shock spectrum as the standard, the energy distribution curves of 9 shock spectrum levels are obtained. These curves display that the shock energy of debris flow focus on the low frequency smaller than 1.0Hz, and the percentage below 6.25Hz is about 95%. The results provide a reference to select wallop peak as the design load of structures against debris flow disaster.

Unsteady Structure Measurement of Cloud Cavitation on a Foil Section Using Conditional Sampling Technique

1989 ◽  
Vol 111 (2) ◽  
pp. 204-210 ◽  
Author(s):  
A. Kubota ◽  
H. Kato ◽  
H. Yamaguchi ◽  
M. Maeda
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Laser Doppler Anemometry ◽  
Low Frequency ◽  
Sampling Technique ◽  
Experimental Result ◽  
Small Scale ◽  
Conditional Sampling ◽  
Cloud Cavitation ◽  
Structure Of Flow

The structure of flow around unsteady cloud cavitation on a stationary two-dimensional hydrofoil was investigated experimentally using a conditional sampling technique. The unsteady flow velocity around the cloud cavitation was measured by a Laser Doppler Anemometry (LDA) and matched with the unsteady cavitation appearance photographed by a high-speed camera. This matching procedure was performed using data from pressure fluctuation measurements on the foil surface. The velocities were divided into two components using a digital filter, i.e., large-scale (low-frequency) and small-scale (high frequency) ones. The large-scale component corresponds with the large-scale unsteady cloud cavitation motion. In this manner, the unsteady structure of the cloud cavitation was successfully measured. The experimental result showed that the cloud cavitation observed at the present experiment had a vorticity extremum at its center and a cluster containing many small cavitation bubbles. The convection velocity of the cavitation cloud was much lower than the uniform velocity. The small-scale velocity fluctuation was not distributed uniformly in the cavitation cloud, but was concentrated near its boundary.

NSCT-Based Multi-Sensor Image Fusion Algorithm

2013 ◽  
Vol 347-350 ◽  
pp. 3212-3216
Author(s):  
Hai Feng Tan ◽  
Wen Jie Zhao ◽  
De Jun Li ◽  
Tian Wen Luo
Keyword(s):  
Image Fusion ◽  
Average Method ◽  
Low Frequency ◽  
Weighted Average ◽  
Inverse Transformation ◽  
Fusion Image ◽  
Fusion Algorithm ◽  
Regional Energy ◽  
Focus Image ◽  
Quantitative Indicators

Against the defects that the favoritism method and average method in the multi-sensor image fusion are apt to impair the image contrast, an image fusion algorithm based on NSCT is proposed. Firstly, this algorithm applied NSCT to the rectified multi-sensor images from the same scene, then different fusion strategies were adopted to fuse the low-frequency and high-frequency directional sub-band coefficients respectively: regional energy adaptive weighted method was used for low-frequency sub-band coefficient; the directional sub-band coefficient adopted a regional-energy-matching program that combined weighted average method and selection method. Finally, the fusion image was obtained by NSCT inverse transformation. Experiments were conducted to IR and visible light image and multi-focus image respectively. And the fusion image was evaluated objectively. The experimental results show that the fusion image obtained through this algorithm has better subjective visual effects and objective quantitative indicators. It is also superior to the traditional fusion method.

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