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In computer vision, many applications could greatly benefit from multi-spectral image data. Our aim is to illustrate the effectiveness of multi-spectral analysis obtained from a simple and cost-effective system. While the proposed approach is broadly applicable, in this paper we focus on the specific case of skin detection. To obtain the multi-spectral data, we have assembled a system using multiple...
A novel method for detecting edges and lines simultaneously and automatically is proposed. This method, based on phase congruency and tensor voting (hence PCTV), makes use of the properties of how edges and lines are built from the Fourier decomposition of an image, and how the primary visual cortex responds to them, instead of making assumptions on the intensity profiles of the regions near a feature...
This paper proposes to apply a high-resolution time-frequency analysis (TFA) algorithm, the matching pursuit (MP), to extract and identify detail components of somatosensory evoked potential (SEP) signals. Conventional TFA methods showed limited time-frequency resolution in short-period nonstationary SEP signals so that they cannot reveal detail components in time-frequency domain. The MP algorithm...
In this paper, a new non-regularization method for positron emission tomography (PET) reconstruction is proposed. The proposed method is a feature-based method using Fourier-Wavelet basis. In order to obtain the reconstructions, we have to calculate the Fourier-Wavelet moment (FWM) from the measurements. To achieve this, iterative method is employed. The rotation invariance property of the proposed...
In this paper, a new non-regularization method for positron emission tomography (PET) reconstruction is proposed. The proposed method is a feature-based method using Fourier-Wavelet basis. In order to obtain the reconstructions, we have to calculate the Fourier-Wavelet moment (FWM) from the measurements. To achieve this, iterative method is employed. The rotation invariance property of the proposed...
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