A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative ...
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A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing.
This paper proposes a novel method to determine the speed of the surrounding vehicles in traffic scenarios. Relying on the video information obtained from a stereo camera mounted on a moving vehicle, we first determin...
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We present a method for tracking deformable surfaces in 3D using a stereo rig. Different from traditional recursive tracking approaches that provide a strong prior on the pose for each new frame, the proposed method t...
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This paper focuses on recognizing the individual Tamil characters in images of natural scenes. Even though natural character dataset are available publicly for different languages, no specific standardized dataset is ...
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A multi-character recognition method based on hidden Markov model （HMM） was presented. The method can reduce the calculation load of correlation and improve recognition accuracy compared with singlecharacter recogni...
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A multi-character recognition method based on hidden Markov model （HMM） was presented. The method can reduce the calculation load of correlation and improve recognition accuracy compared with singlecharacter recognition in video. The characteristics used for recognizing include the shape character, the color character, the texture character and so on. Even our human being generally uses these characteristics to recognize objects in practice..4, recognition experiment of 17 fishes was carried out in the paper. The experimental results demonstrate the high veracity of the multi-character recognition algorithm. Together with the tracking process, it can handle dynamic objects, so the multi-character recognition is more like the human recognition, and has great application value.
This paper introduces a shape descriptor based on a combination of topological image analysis and texture information. Critical points of a shape’s skeleton are determined first. The shape is described according to p...
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We present a novel neural network model for visual information processing. The model uses a hierarchical network with local connectivity (image pyramid) as a stem network. This network generates hypotheses about the e...
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Sparse representation has recently been proved to be a powerful tool in imageprocessing and object *** paper proposes a novel small target detection algorithm based on this *** modelling a small target as a linear co...
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Sparse representation has recently been proved to be a powerful tool in imageprocessing and object *** paper proposes a novel small target detection algorithm based on this *** modelling a small target as a linear combination of certain target samples and then solving a sparse 0-minimization problem,the proposed apporach successfully improves and optimizes the small target representation with ***,the sparsity concentration index（SCI） is creatively employed to evaluate the coefficients of each block representation and simpfy target *** the detection frame,target samples are firstly generated to constitute an over-complete dictionary matrix using Gaussian intensity model（GIM）,and then sparse model solvers are applied to finding sparse representation for each sub-image ***,SCI lexicographical evalution of the entire image incorparates with a simple threshold locate target *** effectiveness and robustness of the proposed algorithm are demonstrated by the exprimental results.
The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, w...
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In this paper,we use 1D rotating objects to calibrate *** calibration object has three collinear *** is not necessary for the object to rotate around one of its endpoints as before;instead,it rotates around the middle...
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In this paper,we use 1D rotating objects to calibrate *** calibration object has three collinear *** is not necessary for the object to rotate around one of its endpoints as before;instead,it rotates around the middle point in a *** this instance,we can use two calibration constraints to compute the intrinsic parameters of a *** addition,when the 1D object moves in a plane randomly,the proposed technique remains valid to compute the intrinsic parameters of a *** with simulated data as well as with real images show that our technique is accurate and robust.
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