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Blur detection in a single image is challenging especially when the blur is spatially-varying. Developing discriminative blur features is an open problem. In this paper, we propose a new kernel-specific feature vector consisting of the information of a blur kernel and the information of an image patch. Specifically, the kernel specific-feature is composed of the multiplication of the variance of filtered...
Focus on the issue of rotation and scale in-variance for remote sensing image(RSI) segmentation, a feature extraction and classification method is proposed based on differential space. A RSI is divided into many regions with different size, and all the covariance matrices of each region are calculated. Those covariance matrices construct a connected Riemannian manifold. The map relation between the...
In feature gene selection, filtering model concerns classification accuracy while ignoring gene redundancy problem. On the other hand, gene clustering finds correlated genes without considering their predictive abilities. It is valuable to enhance their performances by the help of each other. We report a new feature gene extraction algorithm, namely double-thresholding extraction of feature gene (DEFG),...
According to the nature scenes, a method for detecting and tracking of moving target based on Curve-Flows is proposed, which selects threshold automatically, extracts targetpsilas textures and calculates their curve-flows. It can locate static objects; estimate the movement information of those moving objects by analyzing the curve-flows fields. The method can distinguish a target that similar highly...
An object recognition method for agent, indoor mobile robot for instance, is presented based on feature-line flows. Considering the surrounding of indoor scenes, we extract the feature lines from image sequence captured through camera by using Radon Transform, and then calculate their optical flows; Secondly, process those flows through PCA, distinguish moving objects from static objects by computing...
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