Wavelet De-Noising Algorithm Based on OpenCV for Images Edge Detection

2014 ◽  
Vol 989-994 ◽  
pp. 3973-3976
Author(s):  
Yi Fan Ma ◽  
Shu Gui Liu
Keyword(s):  
Edge Detection ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Canny Edge Detection ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Wavelet Algorithm

Image edge detection is easily affected by noise. Wavelet algorithm can divide the image into low frequency and high frequency. By the processing of high frequency signal and the reconstruction of wavelet coefficients, the purpose of removing noise can be achieved. In the environment of VC++6.0, an image de-noising algorithm based on the wavelet combined with the Canny edge detection is proposed, which obtains a good result. The above algorithms are implemented based on OpenCV, which is more efficient, providing the conditions for subsequent image analysis and recognition. Experiments are carried out and the results show that the proposed algorithm is available and has a good performance.

Research on Improvement Algorithm of Image Edge Detection

2014 ◽  
Vol 539 ◽  
pp. 141-145
Author(s):  
Shui Li Zhang
Keyword(s):  
Cognitive Psychology ◽  
Edge Detection ◽  
High Frequency ◽  
Detection Method ◽  
Low Frequency ◽  
Frequency Information ◽  
Image Edge Detection ◽  
Improvement Algorithm ◽  
Image Edge ◽  
Edge Detection Method

This paper presents new theorems Stevens edge detection method based on cognitive psychology on. Firstly, based on the number of the image is decomposed into high-frequency and low-frequency information, and the high-frequency information extracted by subtracting the maximum number of images to the image after the filter, then the amount of high frequency information into psychological cognitive psychology based on Stevenss theorem. The algorithm suppression refined edge after the non-minimum, applications Pillar K-means algorithm to extract image edge. Experimental results show that: the brightness of the image is converted to the amount of psychological edge can better unify under different brightness values.

A Study on Parallel and Pipelining Simulation Techniques for Edge Detection and Their Performance Analysis

2019 ◽  
Vol 16 (2) ◽  
pp. 568-572
Author(s):  
Merlin L. M. Livingston ◽  
Senthil C. Singh ◽  
K. Manojkumar ◽  
Sathish S. Kumar
Keyword(s):  
Edge Detection ◽  
Prime Number ◽  
Parallel Simulation ◽  
Canny Edge Detection ◽  
Simulation Techniques ◽  
Image Edge Detection ◽  
Multi Stage ◽  
Canny Edge ◽  
Image Edge ◽  
Sobel Edge Detection

Real processing components along with component simulators are combined together to construct a new virtual prototyping system. The increase in component simulators result in degraded performance of the simulation in distributed systems. The speed of simulation can be increased by doing parallel simulation techniques. Prime number test and Image edge detection are chosen to implement the parallel simulation techniques and achieved the expected results while implementing in real time applications. The prime number test calculates the number of processors in a system and the image edge detection can be done in two stages by Canny Edge detection and Sobel Edge detection. The Canny Edge detection is used to detect the edges in the images by using a multi-stage algorithm. The smaller, separable and integer valued filter in images are combined in horizontal and vertical directions by using the Sobel edge detection resulting in reduction of implementation cost. The tool named OpenMP is used for implementing the parallel simulation techniques by combining both the canny edge and Sobel edge detection. An add-on named MPI is used along with the OpenMP to reduce the implementation time in parallel processing.

Research on Edge Detection Technology

2013 ◽  
Vol 860-863 ◽  
pp. 2884-2887 ◽  
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Hai Yan Wang
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Canny Edge Detection ◽  
Detection Techniques ◽  
Image Edge Detection ◽  
Detection Technology ◽  
Canny Edge ◽  
Important Field ◽  
Image Edge ◽  
Better Than

Edge detection is an important field in image processing. Edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection techniques. Various image edge detection techniques are introduced. These techniques are compared by using MATLAB7.0. The qualities of these techniques are elaborated. The results show that Canny edge detection techniques is better than others.

Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition

2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Rock Interface ◽  
Coal Rock ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.

An Improved Edge Detection Algorithm Based on Canny Operator

2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Image Simulation ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.

scholarly journals An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan
Keyword(s):  
Machine Tool ◽  
Frequency Domain ◽  
Surface Topography ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Time Frequency ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

scholarly journals Identification of Image Edge Using Quantum Canny Edge Detection Algorithm

2019 ◽  
Vol 13 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Dini Sundani ◽  
◽  
Sigit Widiyanto ◽  
Yuli Karyanti ◽  
Dini Tri Wardani ◽  
...  
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

scholarly journals 3D Image Edge Detection Algorithm for Depth Detection

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3555-3557
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
3 Dimensional ◽  
3D Objects ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
3D Scene ◽  
Edge Recognition

Showing a genuine 3 dimensional (3D) objects with the striking profundity data is dependably a troublesome and cost-devouring procedure. Speaking to 3D scene without a noise (raw image) is another case. With a honed technique for survey profundity measurement can be effortlessly gotten, without requiring any extraordinary instrument. In this paper, we have proposed an edge recognition process in a profundity picture dependent on the picture based smoothing and morphological activities.In this strategy, we have utilized the guideline of Median sifting, which has a prestigious element for edge safeguarding properties. The edge discovery was done dependent on the Canny Edge Detection Algorithm. Along these lines this strategy will help to identify edges powerfully from profundity pictures and add to advance applications top to bottom pictures

Sub-Pixel Edge Detection for Precision Measurement Based on Canny Criteria

2005 ◽  
Vol 295-296 ◽  
pp. 711-716 ◽  
Author(s):  
S.H. Xie ◽  
Qiu Liao ◽  
S.R. Qin
Keyword(s):  
Edge Detection ◽  
Precision Measurement ◽  
High Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Interpolation Algorithm ◽  
Interpolation Scheme ◽  
Initial Image ◽  
Canny Edge Detection ◽  
Canny Edge

A new nonlinear intensity interpolation algorithm is presented to realize sub-pixel edge detection. The interpolation algorithm based on the Canny criteria makes full use of grads information attained by Canny edge detection to perform special interpolation in the grads direction. When the resolution is enhanced, the interpolated image by the new interpolation scheme can efficiently preserve high frequency component in the original image. The edge detection of interpolated image permits high precision localization. The new interpolation algorithm is more effective in reserving the grads information of the step edge of the initial image than the usual linear interpolations. It requires simpler computation than the present non-linear interpolations.

Vibrational resonance in a discrete neuronal model with time delay

2014 ◽  
Vol 28 (16) ◽  
pp. 1450103 ◽  
Author(s):  
Canjun Wang ◽  
Keli Yang ◽  
Shixian Qu
Keyword(s):  
Time Delay ◽  
Input Signal ◽  
High Frequency ◽  
Phase Synchronization ◽  
Low Frequency ◽  
Neuronal Model ◽  
Vibrational Resonance ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Neuron System

The effects of time delay on the vibrational resonance (VR) in a discrete neuron system with a low-frequency signal and a high-frequency signal are investigated by numerical simulations. The results show that there exists a delay time that optimizes the phase synchronization between the low-frequency input signal and the output signal. VR is induced by the time delay. Furthermore, the time delay can improve the response to a low-frequency input signal. Therefore, the time delay plays a constructive role in the transmission of a low-frequency signal by inducing and enhancing VR.

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