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This paper proposes a multi-feature extraction algorithm aiming to recognize disturbances by analyzing synchrophasor data from wide-area monitoring systems. The novel algorithm utilizes wavelet transform (WT) to extract preliminary features from synchrophasors. Two types of features are created by organizing scaling coefficients and wavelet coefficients from WT. The multi-features are compressed by...
For early fire detection, smoke is considered as an important sign for it. Image based detection methods more useful than other methods which use some special sensor devices because of the cost and difficulties in setting them around target areas. When treating the image information of smoke, it is important to consider characteristics of smoke such as the semi-transparency, the non-stationary shape...
Boundary roughness of skin lesions is of clinical significance for early detection of malignant melanomas. An integrated approach of local fractals and multi-level wavelet analysis is proposed in the paper. Local fractal profile of a lesion contour is generated to describe boundary roughness while a tree structured wavelet packet is further processed to give behaviors of the local fractals at different...
Based on multifractal analysis in wavelet pyramids of texture images, a new texture descriptor is proposed in this paper that implicitly combines information from both spatial and frequency domains. Beyond the traditional wavelet transform, a multi-oriented wavelet leader pyramid is used in our approach that robustly encodes the multi-scale information of texture edgels. Moreover, the resulting texture...
Considering the image compressibility and the error allowance of decoded image, this paper presents a high-capacity image watermark method based on fractal compression in the wavelet transform domain. Fractal compression technique is used to encode a gray image and the fractal codes are embedded into the wavelet coefficients of the gray image according to well-connected watermark algorithm. After...
In this paper, a multi scale Gaussian edge detector is constructed. According to transfer properties across scales of the wavelet modules of the signal edge and the noise edge, we combine the properties of edges in different scales and propose a multi scale edge fusion algorithm consisting of edge transfer, edge inherit and edge growth. The edge is an important content of obtaining information of...
Frequency is a vital factor for power system operation and protection. This paper is on extraction of frequency feature for fault/event analysis based on wavelet transform (WT) and fractal geometry (FG). The frequency signal is decomposed by WT-based multiresolution analysis (MRA) and a family of wavelet coefficients is obtained. A maxima line is constructed by connecting the maximum point in the...
A pixel-level fusion approach is proposed to refine the resolution of urban multi-spectral images using the corresponding high-resolution panchromatic images. After the two images are decomposed by wavelet transform, three texture features are extracted from high-frequency detailed sub-images. Then a fuzzy fusion rule is used to merge wavelet coefficients from the two images according to the extracted...
This paper present a wavelet-fractal dimension approach for extracting feature from ultrasonic non-destructive evaluation (NDE) data of a test multilayer adhesive structure specimen. These features are then used to estimate the specimen's bonded quality. When the multilayer adhesive structure undergo ultrasonic NDE, echo from interior layers often overlap severely, causing information from individual...
By combining wavelet transform (WT) with fractal theory, a novel approach is put forward to detect early short-circuit fault and analyze voltage stability. The application of signal denoising based on the statistic rule is brought forward to determine the threshold of each order of wavelet space, and an effective method is proposed to determine the decomposition level adaptively, increasing the signal-noise-ratio...
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