Showing papers on "Wavelet transform modulus maxima method published in 2012"
Journal Article•
TL;DR: The experimental comparison of the improved edge detection method with gray value mathematical morphology with wavelet transform modulus maxima method with the results verify the feasibility and validity of the method.
Abstract: In a noisy image,it is difficult to comprehensively consider the aspects of edge orientation,noise restraint,weak edge reservation and vision sense of edge detail,so a method of edge detection based on image fusion is proposed in this paperFirstly,the method of image edge detection based on wavelet transform modulus maxima is discussedCombining the basic operation of mathematical morphology with information entropy theory,an improved edge detection method with gray value mathematical morphology is proposed,and its basic principle is analyzedSecondly,the final better image edge is obtained by adopting superposition operation to fuse the image edges obtained by the both methodsFinally,the experimental comparison of our method with traditional edge detection methods,wavelet transform modulus maxima method and improved gray value mathematical morphology method has been implemented and the results verify the feasibility and validity of our method
3 citations
6 Nov 2012
TL;DR: The result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization.
Abstract: By using wavelet transform modulus maxima method to detection image edge, edge details are easily smoothed out in the large scale analysis and related parameters great influenced by the noise is not easy to extract in traditional small scale analysis To solve this problem, this paper proposes a method based on one-dimensional discrete wavelet image edge detection This algorithm decompose image into one-dimensional signal, making signal-noise separation with one-dimensional discrete wavelet, and detect the edge of de-noised signal's high frequency components The article has experimented the multiple vehicle detection in real scene for many times, and the result shows that this algorithm solved the problem that exist in wavelet transform modulus maxima method to test image edges in small scale analysis, restraining noise better, and had higher precision in edge localization
1 citations
Patent•
8 Jun 2012
TL;DR: The invention discloses an automatic fault-point locating method for the traveling-wave based fault location of high-voltage electric power lines, which comprises the steps of determining the difference of arrival times of fronts of an initial traveling- Wave, determining the position of a front of a fault-reflected traveled-wave, establishing a standard database of wave velocities of traveling waves, and calculating the distance between fault points.
Abstract: The invention discloses an automatic fault-point locating method for the traveling-wave based fault location of high-voltage electric power lines, which comprises the steps of determining the difference of arrival times of fronts of an initial traveling-wave and a fault traveling-wave, determining the position of a front of a fault-reflected traveling-wave, establishing a standard database of wave velocities of traveling waves, and calculating the distance between fault points; and the method is characterized in that the characteristic value of a starting point of the initial traveling-wave is extracted, and then, the starting point of each fault-reflected traveling-wave is calculated by using waveform similarity judging conditions. According to the invention, firstly, traveling-wave signals are picked up when an electric power line has a fault, and the traveling-wave signals subjected to analog-to-digital conversion are imputed into a PC (personal computer) or an embedded system; then, through sequentially adopting a FFT (fast Fourier transform algorithm) method, a FIR (finite impulse response) filtering method, a wavelet analysis method, a wavelet packet analysis method, a wavelet transform modulus maxima method and a derivation algorithm, an operation of de-noising processing on traveling-wave test data is performed so as to eliminate the influence of interfered traveling waves. On this basis, the arrival times of the fronts of the initial traveling-wave and the fault traveling-wave are accurately obtained, and then through combining with the calculation and analysis on the wave velocities of traveling waves, the accurate locating of fault points is realized.