Blind separation of independent sources from their nonlinear convoluted mixtures is a more realistic problem than from linear ones. A solution to this problem based on the Entropy Maximization principle is presented. ...
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Blind separation of independent sources from their nonlinear convoluted mixtures is a more realistic problem than from linear ones. A solution to this problem based on the Entropy Maximization principle is presented. First we propose a novel two-layer network as the de-mixing system to separate sources in nonlinear convolved mixture. In output layer of our network we use feedback network architecture to cope with convoluted mixtures. Then we derive learning algorithms for the two-layer network by maximizing the information entropy. Based on the comparison of the computer simulation results, it can be concluded that the proposed algorithm has a better nonlinear convolved blind signal separation effect than the H.H. Y' s algorithm.
Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occup...
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Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.
A color-based visual technique is described based on the mean shift image segmentation method providing relevant information for robust localization of the visible road area in Urban Intelligent Transportation System ...
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A color-based visual technique is described based on the mean shift image segmentation method providing relevant information for robust localization of the visible road area in Urban Intelligent Transportation System (U-ITS). The traffic image sequences are firstly trained to extract the background and then segmented into separated parts by the mean shift method as initialization, regions with the number of pixels not less than a threshold and with more uniform surfaces with the 'same' color compared to their environment are filtered as recognized road area. The algorithm given in this paper can present road area recognition with arbitrary shapes, which is fit for unstructured road applications in urban cities very well.
A new method for natural color image segmentation using integrated mechanism is proposed in this paper. Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to ...
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A new method for natural color image segmentation using integrated mechanism is proposed in this paper. Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to label long edge lines based on the global color information to estimate roughly the distribution of objects in the image, while short ones are merged based on their positions and local color differences to eliminate the negative affection caused by texture or other trivial features in image. Region growing technique is employed to achieve final segmentation results. The proposed method unifies edges, whole and local color distributions, as well as spatial information to solve the natural image segmentation problem. The feasibility and effectiveness of this method have been demonstrated by various experiments.
In this paper, two new similarity measure methods based on set theory were proposed. Firstly, similarity measure of two sets based on set theory and set operation was discussed. This principle was used to spectral vec...
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In this paper, two new similarity measure methods based on set theory were proposed. Firstly, similarity measure of two sets based on set theory and set operation was discussed. This principle was used to spectral vectors, and two approaches were proposed. The first method was to create a spectral polygon corresponding to spectral curve, and similarity of two spectral vectors can be replaced by that of two polygons. Area of spectral polygon was used as quantification function and some effective indexes for similarity and dissimilarity were computed. The second method was to transform the original spectral vector to encoding vector according to absorption or reflectance feature bands, and similarity measure was conducted to encoding vectors. It proved that the spectral polygon-based approach was effective 'and can be used to hyperspectral RS image retrieval.
This paper illustrates the performance of a mobile positioning technique applicable to a GSM *** experimental system of a network-based GSM positioning for ITS has been proposed, and the hybrid TOA-TDOA method based o...
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This paper illustrates the performance of a mobile positioning technique applicable to a GSM *** experimental system of a network-based GSM positioning for ITS has been proposed, and the hybrid TOA-TDOA method based on GSM signaling has been analyzed and used. The performance of the proposed system is showed through simulations in urban and suburban environments. The accuracy for 67% mobile stations is 70 m in urban and 120 m in suburban. The accuracy, coverage and network load of positioning system are also analyzed.
Object-based video segmentation is an important issue for many multimedia applications. A video segmentation method based on EM algorithm is proposed. We consider video segmentation as an unsupervised classification p...
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Object-based video segmentation is an important issue for many multimedia applications. A video segmentation method based on EM algorithm is proposed. We consider video segmentation as an unsupervised classification problem and apply EM algorithm to obtain the maximum-likelihood estimation of the Gaussian model parameters for model-based segmentation. We simultaneously combine multiple features (motion, color) within a maximum likelihood framework to obtain accurate segment results. We also use the temporal consistency among video frames to improve the speed of EM algorithm. Experimental results on typical MPEG-4 sequences and real scene sequences show that our method has an attractive accuracy and robustness.
The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination ...
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The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination technologies are introduced and the characteristics of GSM useful for location determination are also summarized. An experimental positioning system based on GSM is proposed, and the architecture is described. TOA method based on GSM signals and TDOA method are used in the experimental system. Moreover, the methods are simulated. The performance of the positioning methods is assessed in the simulation environment, and the accuracy for 67% mobile stations (MS) is 70m in urban areas.
A new trend in the development of medical imageprocessing systems is to enhance the shar-ing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medica...
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A new trend in the development of medical imageprocessing systems is to enhance the shar-ing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medical image dynamic collaborative processing on the distributed environment by combining the JAVA, CORBA (Common Object Request and Broker Architecture) and the MAS (Multi-Agents System) collaborative mechanism. The architecture allows medical specialists or applications to share records and cornmunicate with each other on the web by overcoming the shortcut of traditional approach using Common Gateway Interface (CGI) and client/server architecture, and can support the remote heterogeneous systems collaboration. The new approach im-proves the collaborative processing of medical data and applications and is able to enhance the in-teroperation among heterogeneous system. Research on the system will help the collaboration and cooperation among medical application systems distributed on the web, thus supply high quality medical service such as diagnosis and therapy to practicing specialists regardless of their actual geo-graphic location.
Support vector machine (SVM), as a novel approach in patternrecognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with ...
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Support vector machine (SVM), as a novel approach in patternrecognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-
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