This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our meth...
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This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.
Guided by a building concept model, which interprets building into different levels and scales, this paper presents a method to extract buildings in monocular urban aerial images without priori illuminating or orienta...
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ISBN:
(纸本)0780381939
Guided by a building concept model, which interprets building into different levels and scales, this paper presents a method to extract buildings in monocular urban aerial images without priori illuminating or orientation knowledge. By using a shadow context model, a method was proposed to estimate the direction of shadow cast to verify the raw segmentations. Building extractions are refined by context, and a method of partial snake with the aid of the shadow cast direction is proposed, which can sharply reduce the iteration complexity and the influence caused by illumination. The extraction of self-shadow on gable roof with a proposed mathematical roof model is also discussed in this paper.
A Hopfield neural network approach to blind bilevel image restoration is presented. In the approach, two kinds of Hopfield neural networks are used. One is the analog Hopfield neural network, utilized to estimate the ...
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A Hopfield neural network approach to blind bilevel image restoration is presented. In the approach, two kinds of Hopfield neural networks are used. One is the analog Hopfield neural network, utilized to estimate the parameters of the finite point spread function (PSF) of a blurring system. The other one is the modified Hopfield neural network used to restore bilevel image. The entire model is based on the alternative operation of the two networks. In the modified Hopfield neural network, the eliminating highest error (EHE) criterion is applied for the purpose of obtaining a more precise solution. Simulation results show that, after a few iterations, the model always obtains a bilevel image whose quality is almost the same as, or even better than, what is obtained by the modified Hopfield network when the precise parameters of PSF are used. The results are quite good. If the EHF criterion is not used, the model does not achieve a good bi-level image.< >
Anisotropic diffusion can remove noise to some extent in imageprocessing. However the contradiction between diffusion and preservation still exists. In this paper, a new nonlinear diffusion model for image noise remo...
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Anisotropic diffusion can remove noise to some extent in imageprocessing. However the contradiction between diffusion and preservation still exists. In this paper, a new nonlinear diffusion model for image noise removal and feature preservation is presented. This model treats inhomogeneity region and image feature adaptively by discontinuity measure and local gradient information. A well balance between diffusion and preservation is also made in this new diffusion method. Experiments results show that the proposed method has high performance compared to other literature methods and is an ideal edge-preserving filtering method. In addition, we use block-based noise estimation to estimate deviation in diffusion equation
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from diff...
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The Laplacian of Gaussian operator, Del /sup 2/G, is very important as an edge detector in the theory of computer vision. The bias of zero-crossing and output signal-to-noise-ratio of Del /sup 2/G under the models of ...
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ISBN:
(纸本)0818608781
The Laplacian of Gaussian operator, Del /sup 2/G, is very important as an edge detector in the theory of computer vision. The bias of zero-crossing and output signal-to-noise-ratio of Del /sup 2/G under the models of four typical kinds of edges corrupted by white noise are given, and these theoretical results are confirmed by experiments. The relations among bias of zero-crossing, output and input signal-to-noise-ratio and parameter sigma of Del /sup 2/G are presented.< >
A method for zip code recognition is presented. 2D binary images are input to HAVNET, a neural network which employs the Hausdorff distance as a similarity metric to train the weights which are required to represent t...
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ISBN:
(纸本)0769503187
A method for zip code recognition is presented. 2D binary images are input to HAVNET, a neural network which employs the Hausdorff distance as a similarity metric to train the weights which are required to represent the patterns learned by the network. A new learning rule for HAVNET is also introduced. In this approach, HAVNET is combined with a multilayer neural network. The Hausdorff distance acts as a zip code filter. Only the confusing digits are input into the multilayer network for training or recognition. Experimental results show that the correct-recognition rate with zero rejection is more than 97% for a database used by the Chinese mail sorting system.
In this paper, we analyze the traditional algorithm (Circle->Phase) in the traffic-control system. And we propose a new algorithm that is proved better than the former one. By traffic flow simulation using advanced...
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ISBN:
(纸本)0780381254
In this paper, we analyze the traditional algorithm (Circle->Phase) in the traffic-control system. And we propose a new algorithm that is proved better than the former one. By traffic flow simulation using advanced TSIS software, we get statistic data to analyze the characteristic of downstream traffic flow (DTF). Based on the mathematic model of DTF, we bring forward an algorithm to quickly decide the phase length and circle length. The algorithm adopts the real-time information according to required flow with the aim of minimizing the surplus time in each phase. It can adapt to any kind of traffic flow and has a high degree of flexibility.
Multisensor image registration is a difficult problem. In this paper, we give a new registration method using direct histogram specification technique. We find that after using histogram specification, the resulting i...
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Multisensor image registration is a difficult problem. In this paper, we give a new registration method using direct histogram specification technique. We find that after using histogram specification, the resulting images with the same view look more similar, though the original images gained by different sensors differ much in intensity. Based on this property, a novel approach to find matching block pairs is proposed. The centers of the block pairs are used as control points (cps). We also use the cluster method of the nearest function criterion to test the correctness of the cps and discard wrong ones. The algorithm has been tested by many aerial images of different sensors. The effectiveness is illustrated by the experimental results.
An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar...
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ISBN:
(纸本)0769525210
An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar-like features. The candidates may include false positives and multiple detections. Then, geometrical distribution of facial components is imposed on the candidates to select the optimal configuration. For simplicity, we suppose full dependence between the components and model it with multivariate Gaussian. The effectiveness of the framework is evaluated with experiments
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