Void-layer detection and thickness determination in runways are studied in this paper. Void-layer is thin layer whose thickness is very small (usually less than 1cm). Firstly, the void-layer can be detected based on i...
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Illumination always affects image quality seriously in practice. To weaken illumination effect on image quality, this paper proposes an adaptive Gamma correction method. First, a mapping between pixel and Gamma values...
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Recognition of real world scenes can be efficiently solved based on global features termed the Spatial Envelope. Such features indeed comprise multiple modes such as orientations, scales, sparsity profiles. In order t...
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In order to achieve accurate recognition of human finger vein (FV), this paper addresses the problems of finger vein localization and vein feature extraction. An inherent physical property of human fingers is used to ...
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Contour information always contributes much for object analysis in image processing. In this paper, a new method of constructing contours of skin regions is proposed. To obtain skin regions readily, a region splitting...
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Recently, finger-vein recognition has been studied extensively for personal identification. Since veins exist inside the finger, the finger-vein images are often not in high quality due to light scattering and absorpt...
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In this paper, we propose a tensorial approach to single trial recognition in a EEG-based BCI system related to movement related potentials. In this approach input data are considered as tensors instead of more conven...
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Finger-vein image enhancement is of great importance for finger-vein recognition since the quality of the finger-vein images always is very poor in practice. In this paper, a new method based on orientation field is p...
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We present a recursive estimation technique for recovering FOE (Focus of Expansion) from unreliable motion or optical flow. The estimation of FOE is of importance to the analysis of camera motion, especially, in the c...
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We present a recursive estimation technique for recovering FOE (Focus of Expansion) from unreliable motion or optical flow. The estimation of FOE is of importance to the analysis of camera motion, especially, in the case that the camera motion is purely translational. Our work is based on the observation that there is strong dependence between FOE estimation and motion flows. Therefore, as the FOE depends on the motion flow, a good motion flow can be obtained from accurate FOE. We assume that the camera motion is purely translational and there is no object motion in the scene. The technique used for the elimination of unreliable motion flow is orthogonal regression method. We combine FOE estimation with the elimination algorithm of unreliable motion flows. Experiments using both simulation and real scenes show that our proposed method works robustly under the condition that the percentage of outliers is varying between [0%,20%].
Strong rebar echo which can't be eliminated in tx domain directly will disturb the detection and discrimination of the interested targets like cryptic disasters. This paper presents the application of Hyp-curvelet...
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