This paper outlines the automatic extraction of features of paintings' art movements such as classicism, impressionism and cubism;and introduces a system developed for the classification and indexing of paintings ...
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The optimization of existing sewer systems or making new systems is and will remain one of the key issues in drainage management in our society. The problem consists of minimization of a nonlinear cost function subjec...
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This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is...
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An important class of radiometric degradations we are faced with often in practice is image blurring. Special attention is paid to the recognition of the blurred image by moment invariant approach. Some important rule...
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ISBN:
(纸本)0780385543
An important class of radiometric degradations we are faced with often in practice is image blurring. Special attention is paid to the recognition of the blurred image by moment invariant approach. Some important rules of complex moments for the blurred image are presented. Based on these rules, a useful subset of moment invariants is introduced, that are not affected by the blur, rotation, scale, and translation of the images. The experiments have shown that these invariants can be successfully used in recognition of the blurred image.
In the case of tracking object changing in size, traditional mean-shift based algorithm always leads to poor localization owing to its unchanged kernel-bandwidth. To overcome this limitation, a novel kernel-bandwidth ...
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We propose an adaptive model update mechanism for mean-shift blob tracking. It is novel for us to use self-tuning Kalman filters for estimating object kernel-color distribution, i.e. kernel-histogram. Filtering residu...
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A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applie...
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A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applied to estimate a new diffusion coefficient. Experimental results demonstrate that anisotropic diffusion based on this new erosion operator can efficiently reduce noise and sharpen object boundaries.
Wavelet image denoising has been well acknowledged as an important method of denoising in imageprocessing. This paper describers a new method for the suppression of noise in image by fusing the wavelet denoising tech...
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Wavelet image denoising has been well acknowledged as an important method of denoising in imageprocessing. This paper describers a new method for the suppression of noise in image by fusing the wavelet denoising technique with support vector regression (SVR). Based on the least squares support vector machine (LS-SVM), a new denoising operators used in the wavelet domain are obtained. Simulated noise images are used to evaluate the denoising performance of the proposed algorithm along with the other wavelet-based denoising algorithm. Experimental results show that the proposed denoising method outperforms standard wavelet denoising techniques in terms of the signal-to-noise ratio and the prevented edge information in most cases. It also achieves better performance than the median filter.
Spatial data mining refers to extracting and "mining" the hidden, implicit, valid, novel and interesting spatial or non-spatial patterns or rules from large-amount, incomplete, noisy, fuzzy, random, and prac...
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ISBN:
(纸本)0780384032
Spatial data mining refers to extracting and "mining" the hidden, implicit, valid, novel and interesting spatial or non-spatial patterns or rules from large-amount, incomplete, noisy, fuzzy, random, and practical spatial databases. In which an important issue but remains underdeveloped is to reveal and handle the uncertainties in spatial data mining. In This work, uncertainty of spatial data is briefly analyzed firstly, including the types and origins of uncertainty, their models of measurement and propagation. Then, some uncertainty factors in operation of spatial data mining are discussed and some uncertainty handling methods are adopted, including maximum variance data discretization and fuzzy belief function. Finally, we think the process of spatial data mining can be regarded as a complex system, a linear serial processing system in engineering control systems. An uncertainty propagation model of spatial data mining - fuzzy logic uncertainty propagation model with credibility factor is developed. Moreover, several key problems about uncertainty handling and propagation in spatial data mining are put forward.
Thermal swipe sensor is one of the technologies behind many of today's fingerprint sensors. This paper presents a new direct Fourier-based algorithm for performing swipe fingerprints registration to subpixel accur...
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