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2000 ACM Workshops on multimedia, multimedia 2000

作者： Ioannou, S. Moschovitis, G. Ntalianis, K. Karpouzis, K. Kollias, S. Image Video and Multimedia Laboratory Electrical and Computer Engineering Department National Technical University of Athens Heroon Polytechniou 9 Athens157 80 Greece

ISBN: (纸本)9781581133110

Current multimedia databases contain a wealth of information in the form of audiovisual, as well as text data. Even though efficient search algorithms have been developed for either media, there still exists the need for abstract presentation and summarization of the results of database users' queries. Moreover, multimedia retrieval systems should be capable of providing the user with additional information related to the specific subject of the query, as well as suggest other topics which users with a similar profile are interested in. In this paper, we present a number of solutions to these issues, giving as an example an integrated architecture we have developed, along with notions that support efficient and secure Internet access and easy addition of new material. Segmentation of the video in shots is followed by shot classification in a number of predetermined categories. Generation of users' profiles according to the same categories, enhanced by relevance feedback, permits an efficient presentation of the retrieved video shots or characteristic frames in terms of the user interest in them. Moreover, this clustering scheme assists the notion of "lateral" links that enable the user to continue retrieval with data of similar nature or content to those already returned. Furthermore, user groups are formed and modeled by registering actual preferences and practices;this enables the system to "predict" information that is possibly relevant to specific users and present it along with the returned results. The concepts utilized in this system can be smoothly integrated in MPEG-7 compatible multimedia database systems. Copyright © ACM 2000.

关键词： Abstracting

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A method for restoration of low-resolution document images

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International Journal on Document Analysis and Recognition 2000年第4期2卷 200-210页

作者： Thouin, Paul D. Chang, Chein-I Department of Defense Fort Meade MD 20755 United States Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250 United States

image restoration using resolution expansion is important in many areas of image processing. This paper introduces a restoration method for low-resolution text images which produces expanded images with improved definition. This technique creates a strongly bimodal image with smooth regions in both the foreground and background, while allowing for sharp discontinuities at the edges. The restored image, which is constrained by the given low-resolution image, is generated by iteratively solving a nonlinear optimization problem. Low-resolution text images restored using this technique are shown to be both quantitatively and qualitatively superior to images expanded using the standard methods of linear interpolation and cubic spline expansion. Experimental results demonstrate that text images created by this new algorithm improve optical character recognition accuracy more than images obtained by existing expansion methods. © 2000 Springer-Verlag Berlin Heidelberg.

关键词： Restoration

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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Affine-invariant curve normalization for shape-based retrieval

Affine-invariant curve normalization for shape-based retriev...

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International Conference on Pattern Recognition

作者： Y. Avrithis Y. Xirouhakis S. Kollias Image Video and Multimedia Systems Laboratory Department of Electrical and Computer Engineering National and Technical University of Athens Greece

ISBN: (纸本)0769507506

A novel method for two-dimensional curve normalization with respect to affine transformations is presented in this paper, allowing an affine-invariant curve representation to be obtained without any actual loss of information on the original curve. It can be applied as a pre-processing step to any shape representation, classification, recognition or retrieval technique, since it effectively decouples the problem of affine-invariant description from feature extraction and pattern matching. Curves estimated from object contours are first modeled by cubic B-splines and then normalized in several steps in order to eliminate translation, scaling, skew, starting point, rotation and reflection transformations, based on a combination of curve features including moments and Fourier descriptors.

关键词： Spline Feature extraction Reflection multimedia databases Content based retrieval image retrieval image coding Shape measurement image segmentation multimedia systems

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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International Conference on Information Fusion

作者： M.G. Mostafa A.A. Farag E. Essock Department of Electrical and Computer Engineering Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychology University of Louisville Louisville KY USA

关键词： image registration Neural networks Hyperspectral sensors Remote sensing image reconstruction Geometry Remote monitoring Intelligent sensors Satellites Laser radar

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Unsupervised seed determination for a region-based color image segmentation scheme

Unsupervised seed determination for a region-based color ima...

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IEEE International Conference on image processing

作者： N. Ikonomakis K.N. Pataniotis A.N. Venetsanopoulos Department of Electrical and Computer Engineering Digital Signal & Image Processing Laboratory University of Toronto Toronto ONT Canada University of Toronto Toronto ON CA

ISBN: (纸本)0780362977

A color image segmentation technique is presented for use in coding and/or compression of video-conferencing sequences. The proposed technique utilizes the perceptual HSI (hue, saturation, intensity) color space and incorporates an unsupervised seed determination algorithm that finds the seed pixels that are in the spatial center of the regions in the image. The algorithm employs a hierarchy system where seeds found at the highest level produce the best results. The region growing algorithm uses these seeds to grow regions by appending to each seed pixel those neighboring pixels that satisfy a certain homogeneity criterion. The technique is found to be robust and relatively computationally inexpensive. The effectiveness of the algorithm is found to be much improved over techniques used in the past.

关键词： Color image segmentation Pixel image coding image converters Signal processing image processing Laboratories Robustness Partitioning algorithms

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Unsupervised fully constrained squares linear spectral mixture analysis method for multispectral imagery

Unsupervised fully constrained squares linear spectral mixtu...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： D.C. Heinz Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Subpixel detection and quantification of materials in multispectral imagery presents a challenging problem due to a relatively low number of spectral bands available for analysis in which case the number of spectral bands may be less than the number of materials to be detected and quantified. The problem is even more difficult when the image scene is unknown and no prior knowledge is available. Under this circumstance, the desired information must be obtained directly from the image data. The authors present an unsupervised least squares-based linear mixture analysis method coupled with a band expansion technique for multispectral image analysis. This method allows the authors to extract necessary endmember information from an unknown image scene so that the endmembers present in the image can be detected and quantified. The band expansion technique creates additional bands from the existing multispectral bands using band-to-band nonlinear correlation. These expanded bands ease the problem of insufficient bands in multispectral imagery and can improve and enhance the performance of the proposed method. The experimental results demonstrate the advantages of the proposed approach.

关键词： Least squares methods Spectral analysis Multispectral imaging Layout image analysis Vectors Hyperspectral sensors Hyperspectral imaging Pixel Least squares approximation

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A target-constrained interference-minimized filter for subpixel target detection in hyperspectral imagery

A target-constrained interference-minimized filter for subpi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Hsuan Ren Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Due to significantly improved high spatial and spectral resolution hyperspectral sensors can now uncover many material substances which cannot be resolved by multispectral sensors. However, this also comes at a price that many unknown and unidentified signal sources, referred to as interferers may also be extracted unexpectedly. Such interferers generally introduce additional noise effects on target detection and its factor must be taken into account. The problem associated with this interference is challenging because interference is generally unknown in nature and cannot be identified from an image scene. This paper presents a target-onstrained interference-minimized filter (TCIMF) which does not require to identify interferers, but can minimize the effects caused by interference. In addition, the TCIMF also separates undesired targets from the desired targets so that the TCIMF can eliminate undesired targets while detecting the desired targets and minimizing interfering effects. Most attractively, these three operations can be carried out by a single process in real time implementation.

关键词： Filters Object detection Hyperspectral sensors Layout Hyperspectral imaging Interference constraints image resolution Signal resolution image sensors image analysis

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A rate-distortion approach to wavelet-based encoding of predictive error frames

A rate-distortion approach to wavelet-based encoding of pred...

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IEEE International Conference on image processing

作者： E. Asbun P. Salama E.J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA

We develop a framework for efficiently encoding predictive error frames (PEF) as part of a rate scalable, wavelet-based video compression algorithm. We investigate the use of rate-distortion analysis to determine the significance of coefficients in the wavelet decomposition. Based on this analysis, we allocate the bit budget assigned to a PEF to the coefficients that yield the largest reduction in distortion, while maintaining the embedded and rate scalable properties of our video compression algorithm.

关键词： Rate-distortion Encoding image coding Video compression computer errors Redundancy Wavelet analysis Decoding Scalability Transform coding

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Application of generalized constrained energy minimization approach to urban road detection

Application of generalized constrained energy minimization a...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chinsu Lin Chuin-Mu Wang Chein-I Chang Environmental Monitoring and Planning Laboratory Department of Forestry National Chiayi University Chiayi Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County MD USA

Classification of thematic layers have been used to update digital databases, particularly digital maps which can be accessed on the Internet by a fast growing number of users. One of the most important features in digital maps is traffic patterns and road networks. Unfortunately, due to low spectral and spatial resolutions of satellite imagery, many roads cannot be extracted at pixel level since the width of most urban and rural roads is less than the pixel size. In addition, road spectral signatures vary from pixel by pixel due to natural background. In this paper, an approach combining a subpixel detection method, called generalized constrained energy minimization with a principal component analysis-based fusion technique is proposed for urban road extraction. Experimental results show that the proposed method can effectively detect roads in Landsat TM and SPOT panchromatic images.

关键词： Roads Satellites Pixel image databases Spatial databases Internet Telecommunication traffic Spatial resolution Minimization methods Remote sensing

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