Solving Level Set Equation (LSE) by using the classical methods mostly based on the finite different approximations, normally costs a lot of computer time particularly when processing high dimensional large-scale data...
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In order to resolve the problem incurred by low efficient manual classification of tremendous aurora images, an automatic aurora images classification system for huge dataset application is proposed. First, static aur...
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ISBN:
(纸本)9781424447749
In order to resolve the problem incurred by low efficient manual classification of tremendous aurora images, an automatic aurora images classification system for huge dataset application is proposed. First, static aurora images are decomposed into texture part and cartoon part with a method called Morphological Component Analysis (MCA). Then features extracted from texture part are classified by three classification methods: nearest neighbor (NN), Support Vector Machine (SVM) with RBF kernel and SVM with linear kernel. The experiment exhibited the classification accuracy improved by 10％, of which, the SVM with linear kernel is much faster and is therefore suitable for massive data processing.
In the paper, a new parallel LZW-Like algorithm, bidirectory LZW algorithm (BD-LZW) will be interpreted The new algorithm can be used in data compression/decompression system which runs on multi-microprocessor system,...
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In this paper, we present a robust approach to digital watermarking embedding and retrieval for digital images. The affine-invariant point detector is used to extract feature regions of the given host image. image nor...
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In this paper, we present a robust approach to digital watermarking embedding and retrieval for digital images. The affine-invariant point detector is used to extract feature regions of the given host image. image nor...
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In this paper, we present a robust approach to digital watermarking embedding and retrieval for digital images. The affine-invariant point detector is used to extract feature regions of the given host image. image normalization and dominant gradient orientation alignment are applied to these feature regions to achieve scaling and rotation invariance. Thereafter, watermarks are embedded in these feature regions. The advantage of this proposed approach is demonstrated by a large amount of experiments, which can against different attacks, such as common imageprocessing, rotation, scaling, cropping, and several other affine transformations.
In this paper, we present a robust approach of digital watermarking embedding and retrieval for digital *** new approach works in special domain and it has two major steps: (1) to extract affine co-variant regions, an...
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In this paper, we present a robust approach of digital watermarking embedding and retrieval for digital *** new approach works in special domain and it has two major steps: (1) to extract affine co-variant regions, and (2) to embed watermarks with a novel fuzzy inference *** advantage of this proposed approach is demonstrated by a large amount of experiments, which are mainly against different attacks, such as common imageprocessing, rotation, scaling, cropping, and several other affine transformations.
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