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Depth maps captured by consumer-level depth cameras such as Kinect usually suffer from the problem of corrupted edges and missing depth values. In this paper, an effective approach with the support of guided color images is proposed to tackle this problem. Firstly, an effective two-pass alignment algorithm is used to reliably align the depth edges with color image edges. Then, a new depth map with...
Object-based image retrieval has been an active research topic in the last decade, in which a user is only interested in some object instead of the whole image. As a promising approach, graph-based multi-instance learning has been paid much attention. Early retrieval methods often conduct learning on one graph in either image or region level. To further improve the performance, some recent methods...
A fingerprint image segmentation approach is proposed in this paper. First, a feature called Fingerprint Ridge Intensity (FRI) is described in detail, which employs two intrinsic fingerprint features, that is, ridge orientation and ridge circle, to represent ridge intensity. Then an adaptive segmentation algorithm for FRI is proposed. Finally, a post-processing procedure is proposed to reduce segmentation...
In reality, the paper money number recognition is significant, which can effectively prevent the illegal trade of paper money. First, this paper makes pretreatment to the paper money, and then for the rapidity and accuracy requirements, a new identification method is presented which based on intersection change and the distance difference between the two points of the character on the special location...
Liver segmentation is a prerequisite for liver cancer CAD, and the result of it affects the accuracy rate of feature extraction and recognition of liver cancer directly. Euclidean distance transformation is one of the main methods in medical image segmentation. However, simply using Euclidean distance transformation will lead to some problems, such as over-segmentation and excessively high cost of...
A scheme of segmentation based on low-level and high-level cues is presented. Firstly, image-pyramid is obtained based on segmentation by Weighted Aggregation (SWA), the suitable coarse pixel image is selected to be as low-level segmentation cues. Kernel principal component analysis (KPCA) is used for building the space of shape to represent shape prior knowledge. The coarse pixel image is expressed...
An improved single odor/gas source searching approach using a mobile robot by combining image recognition in complex environments is presented. First, color image segmentation of prospective visual candidates is achieved using support vector machines (SVM). Second, the features of those candidates, such as color, shape and orientation (the posture of the object) are extracted. Third, the robot finds...
In Magnetic Resonance Imaging(MRI), the acquired complex valued data obtained as the inverse Fourier transform of the raw k-space data are corrupted by Gaussian distributed noise. In this letter, we present an adaptive neighborhood selection algorithm by accounting for the spatial context information, calculated in the undecimated wavelet domain. A modified Wiener filter is approached by a novel bivariate...
Label propagation and manifold ranking have been successfully adopted in content-based image retrieval (CBIR) in recent years. However, while the global low-level features are widely utilized in current systems, region-based features have received little attention. In this paper, a novel transductive framework based on correlated probabilistic label propagation is proposed for region-based images...
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