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检索条件"机构=Image Processing Department Computer Software Technology Laboratory"

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Using context and a genetic algorithm for knowledge-assisted image analysis

Using context and a genetic algorithm for knowledge-assisted...

引用

1st International Conference on Semantic and Digital Media Technologies, SAMT 2006

作者： Dasiopoulou, Stamatia Papadopoulos, George Th. Mylonas, Phivos Avrtihis, Yannis Kompatsiaris, Ioannis Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Greece Image Video and Multimedia Laboratory School of Electrical and Computer Engineering National Technical University Athens Greece

In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic algorithm is applied to realize the final annotation. Experiments with images from the beach vacation domain demonstrate the performance of the proposed approach and illustrate the added value of utilizing contextual information.

关键词： Ontology

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Speckle reduction of polarimetric SAR images based on neural ICA

引用

13th International Conference on Neural Information processing, ICONIP 2006

作者： Jian, Ji Zheng, Tian Department of Computer Science and Technology Northwestern Polytechnical University Xi'an 710072 China Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3540464816

The polarimetric synthetic aperture radar (PSAR) images are modeled by a mixture model that results from the product of two independent models, one characterizes the target response and the other characterizes the speckle phenomenon. For the scene interpretation, it is desirable to separate between the target response and the speckle. For this purpose, we proposed a new speckle reduction approach using independent component analysis (ICA) based on statistical formulation of PSAR image. In addition, we apply four ICA algorithms on real PSAR images and compare their performances. The comparison reveals characteristic differences between the studied neural ICA algorithms, complementing the results obtained earlier. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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Robust ICA neural network and application on Synthetic Aperture Radar (SAR) image analysis

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13th International Conference on Neural Information processing, ICONIP 2006

ISBN: (纸本)3540464816

Independent component analysis (ICA) has shown success in the separation of sources in lots of applications. However, in synthenic aperture radar (SAR) images the noise is multiplicative, so the applicability of ICA is seriously reduced. This paper proposes a new robust independent component analysis neural network (RICANN) that improves the robustness of ICA by adding outlier rejection rule. Its application in synthetic aperture radar (SAR) is discussed. The results show the potential usage in SAR image processing problems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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Improving Shape from Focus Using Defocus Information

Improving Shape from Focus Using Defocus Information

引用

International Conference on Pattern Recognition

作者： K.S. Pradeep A.N. Rajagopalan Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras India

ISBN: (纸本)0769525210

Shape from focus (SFF) method determines the degree of focus in a sequence of observations to estimate the shape of a 3-D object. Existing SFF algorithms use an ad hoc interpolation strategy to account for the error due to the finite step-size by which the translational table is moved while capturing the images. We propose an improved SFF method that uses relative defocus blur derived from actual image data to arrive at the final estimates of the shape of the object. A space-variant image restoration scheme is also proposed to obtain a focused image of the 3-D object. The shape estimates as well as the quality of the restored image using the proposed method are superior to that of traditional SFF

关键词： Shape Focusing Cameras Lenses image restoration Interpolation Pixel Polynomials image sensors image processing

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AN EFFICIENT REPRESENTATION OF DIGITAL CURVES WITH LINE SEGMENTS AND ELLIPTICAL ARCS

AN EFFICIENT REPRESENTATION OF DIGITAL CURVES WITH LINE SEGM...

引用

2006 IET International Conference on Visual Information Engineering

作者： C. Paramanand A.N. Rajagopalan Department of Electrical Engineering Image Processing and Computer Vision Laboratory Indian Institute of Technology Chennai India

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ROBUST SPACE-VARIANT SUPER-RESOLUTION

ROBUST SPACE-VARIANT SUPER-RESOLUTION

引用

2006 IET International Conference on Visual Information Engineering

作者： K.V. Suresh A.N. Rajagopalan Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

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Analysis of P300 Classifiers in Brain computer Interface Speller

Analysis of P300 Classifiers in Brain Computer Interface Spe...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： H. Mirghasemi R. Fazel-Rezai M. B. Shamsollahi BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Brain Image and Signal Processing BISP Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance, in this paper, it is shown that the FLD classifiers outperform the SVM classifiers. FLD classifier uses only ten channels of the recorded electroencephalogram (EEG) signals. This makes them a very good candidate for real-time applications. In addition, FLD approach does not need any optimization similar to other methods. In addition, in this paper, it is shown that the efficiency of using Principal Component Analysis (PCA) for feature reduction results in decreasing the time for the classification and increasing the accuracy

关键词： Brain computer interfaces Electroencephalography Support vector machines Support vector machine classification Principal component analysis Band pass filters Digital filters computer interfaces Cities and towns USA Councils

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Assessment of Preprocessing on Classifiers Used in the P300 Speller Paradigm

Assessment of Preprocessing on Classifiers Used in the P300 ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： H. Mirghasemi M. B. Shamsollahi R. Fazel-Rezai BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Department of Electrical and Computer Engineering Brain Image and Signal Processing Laboratory University of Manitoba Winnipeg MAN Canada

Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper. We used data set lib from the BCI competition 2003 for training and testing phase. Our accuracy varied between 80% and 96%. In our work, we demonstrated that the problems of choosing the classifier and preprocessing methods are not independent of each other. Two of our approaches could achieve the 96% accuracy i.e. 31 of 32 characters were predicted correctly. These two approaches have different classifier and different preprocessing method. It means that the performance of each classifier can be enhanced with a specific preprocessing method. In our approach, we used only three electrodes of 64 applied electrodes. Therefore it can noticeably reduce the time and cost of EEG measurement

关键词： Electroencephalography Band pass filters Filtering Electrodes Testing Noise reduction Feature extraction Principal component analysis Digital filters Cities and towns

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High SNR flexible top hat monopole probe for 1.5 T MRI

High SNR flexible top hat monopole probe for 1.5 T MRI

引用

作者： Mohammadzadeh, M. Shahabadi, M. Soltanian-Zadeh, H. Tavakoli, A. Rafiei, B. Javidnia, D. Oghabian, M.A. Department of Physics Amir-Kabir University of Technology Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Electrical Engineering Amir-Kabir University of Technology Tehran Iran Medical Imaging Center Imam Khomeyni Hospital Tehran Iran Research Center for Science and Technology in Medicine Tehran University of Medical Sciences Tehran Iran

In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and compared with the conventional monopole probe. The top hat probe is constructed by removing a segment of the shield of a coaxial cable. A flexible thin copper foil in contact with the inner conductor of the cable is added to the end section of the cable. The copper foil acts as an antenna top hat load increasing the uniformity of the current distribution on the probe and establishes a uniform region of SNR distribution around the probe. Improvement of the SNR distribution of the top hat probe relative to the conventional monopole probe is evaluated using quantitative indices. Experimental results show that for the top hat probe, the ratio of the maximum image SNR to its relative standard deviation (SR) is 2.73 times higher than that of a conventional probe. © 2006 IOP Publishing Ltd.

关键词： Medical imaging

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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

引用

IEEE International Conference on computer Vision Systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models image edge detection Laboratories

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