Faults of sensor data will always present in sensor networks because of unreliable communication links, measurement interference and harsh environment. Developing fusion algorithms that can tolerate faults is necessar...
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ISBN:
(纸本)9781849191388
Faults of sensor data will always present in sensor networks because of unreliable communication links, measurement interference and harsh environment. Developing fusion algorithms that can tolerate faults is necessary for reliable sensor network applications. In this paper, we study the fault tolerant fusion for moving vehicle classification based on Marzullo's interval fusion algorithm. The unreliable sensor data are represented using interval estimations. To reduce communication cost, quantized interval representation is adopted. Simulation results demonstrate the validity of the interval fusion algorithm. By using quantized representation, the communication cost is reduced.
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.
In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and con...
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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.
In this paper we propose a method for segmenting characters in multispectral images of ancient documents. Due to the low quality of the document images the main idea of our study is to combine the multispectral behavi...
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With extracted local features of a given image, computing its global feature under perceptual framework has shown promising performance in object recognition. However, under some tough applications with large intra-cl...
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Content-based image retrieval plays a key role in the management of a large image database. However, the results of existing approaches are not as satisfactory for the gap between visual features and semantic concepts...
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This paper proposes a novel method for object-based classification in very high spatial resolution aerial image. It combines the saliency maps very closely to extract the conspicuous local regions for better descripti...
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The automatic calibration of the intrinsic camera parameters such as the focal length and the camera orientation is an important pre-requisite for many computer vision algorithms in video surveillance. Despite its imp...
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This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the step...
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