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检索条件"机构=Computer Vision and Image Processing Laboratory Electrical and Computer Engineering"

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Thresholding video images for text detection

Thresholding video images for text detection

引用

作者： Du, Eliza Yingzi Chang, Chein-I Thouin, Paul D. 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 Department of Defense Fort Meade MD 20755

Thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholdging video images is far more difficult than thresholding document images and simple histogram-based methods generally do not perform well. © 2002 IEEE.

关键词： Video signal processing

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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

引用

Congress on Evolutionary Computation

作者： Yin Yee Wai Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be determined uniquely unless some constraints are imposed. Coplanar motion is a popular constraint adopted for this purpose. If the captured motion is not coplanar, only two possible solutions can be obtained at the best even the actual size of the object is given. Therefore, the motion cannot be captured without resolving the distances of each control point from the image plane. By assuming smooth transition, the problem is formulated as one minimizing the transition between image frames and the application of GA to solve this optimization problem is proposed.

关键词： Genetic algorithms Humans Cameras image resolution image sequences Animation Motion analysis Optical filters Optical recording Optical sensors

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Multi-aspect pattern classification using predictive networks and error mapping

Multi-aspect pattern classification using predictive network...

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International Joint Conference on Neural Networks (IJCNN)

作者： J. Salazar M. Robinson M.R. Azimi-Sadjadi Signal/Image Processing Laboratory Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA

A classification scheme is developed for classifying underwater mine-like and non-mine-like objects from acoustic backscattered signals. This scheme uses a predictive network along with a neural network classifier. Th... 详细信息

关键词： Pattern classification Underwater acoustics Fusion power generation Signal processing Neural networks Acoustic signal detection Probability computer errors Laboratories Acoustical engineering

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Unsupervised Kalman filter approach to signature estimation for remotely sensed imagery

Unsupervised Kalman filter approach to signature estimation ...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

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

ISBN: (纸本)078037536X

The commonly used linear spectral unmixing is generally performed on a single pixel basis and does not take advantage of inter-pixel spatial correlation. The Kalman filter has been considered to extend the linear unmixing by taking into account both spectral and spatial correlation. In addition to a linear mixture model implemented as a measurement equation, it includes a state equation to keep track of changes in between pixels. However, Kalman filtering requires the complete knowledge of image endmembers present in image data, which is generally not available and very difficult to obtain a priori. In order to relax this dilemma, this paper presents an unsupervised Kalman filtering (UKF) approach to signature estimation for remotely sensed images. It first uses an anomaly detector combined with orthogonal subspace projection (OSP) to extract desired image endmember signatures directly from the image data, then further applies a discrimination measure to classify the extracted signatures into a set of distinct signatures that will be used in the measurement equation. In order for the UKF to effectively capture spatial correlation among sample image pixels, the state equation is also implemented dynamically to adjust the state transition matrix adaptively. Experimental results have shown that the proposed UKF approach provides additional advantages over the commonly used spectral-based linear unmixing methods.

关键词： Pixel Equations Kalman filters Filtering Nonlinear filters Data mining Remote sensing Detectors Signal processing image processing

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Error resilience of video transmission by rate-distortion optimization and adaptive packetization

Error resilience of video transmission by rate-distortion op...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yuxin Liu P. Salama E. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis Indianapolis IN USA

We propose new schemes to introduce error resilience into the compressed video bitstreams for transmission over packet networks. First, we develop an adaptive packetization scheme that prohibits any dependency across packets, for error resilience purposes, while exploiting the dependency within each packet to improve the source coding performance. Secondly, we address a two-layer rate-distortion optimization scheme to serve our packetization method. We also use forward error correction (FEC) coding across packets to provide further error protection. Finally, we present a simplified version of our schemes to make it fully compliant with the current ITU video coding standard - H.263+.

关键词： Resilience Rate-distortion image coding Video compression computer errors Propagation losses Motion estimation Forward error correction Video coding Streaming media

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

引用

International Conference on Pattern Recognition

作者： Xie Jun H.T. Tsui Xia Deshen Image Processing and Computer Vision Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China Pattern Recognition Laboratory Department of Computer Science Nanjing University of Science and Technology China

ISBN: (纸本)076951695X

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties. The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. The performance in the experiments is better than those of two popular methods.

关键词： Object segmentation Maximum likelihood estimation image segmentation Layout Uncertainty image edge detection Shape measurement image processing Pattern recognition Gaussian distribution

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Thresholding video images for text detection

Thresholding video images for text detection

引用

16th International Conference on Pattern Recognition, ICPR 2002

作者： Du, Eliza Yingzi Chang, Chein-I Thouin, Paul D. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Department of Defense Fort MeadeMD20755 United States

ISBN: (纸本)0769516963

Thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholdging video images is far more difficult than thresholding document images and simple histogrambased methods generally do not perform well. © 2002 IEEE.

关键词： Pattern recognition

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Automatic thresholding abundance fractional images for mixed pixel classification

Automatic thresholding abundance fractional images for mixed...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shao-Shan Chiang Chein-I Chang Department of Electrical Engineering Lunghwa University of Science and Technology Taoyuan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

Mixed pixel classification is different from spatial-based image classification in the sense that the former deals with abundance fractional images resulting from mixed pixels as opposed to classification maps produced by the latter. As a result, mixed pixel classification is generally carried out by visual inspection on the generated abundance fractional images. Consequently, it can be very subjective and vary with different human interpretations. Under such circumstance, it is difficult to substantiate an algorithm and conducting a comparative analysis is impossible. This paper presents one histogram-based approach to thresholding abundance fractional images. It thresholds an abundance fractional image into a binary image using a probability of confidence as a threshold value.

关键词： Pixel Humans image analysis Inspection image segmentation Signal processing image processing Laboratories computer science image classification

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3-D Bayesian ultrasound breast image segmentation using the EM/MPM algorithm

3-D Bayesian ultrasound breast image segmentation using the ...

引用

IEEE International Symposium on Biomedical Imaging

作者： L.A. Christopher E.J. Delp C.R. Meyer P.L. Carson Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Radiology University of Michigan Ann Arbor MI USA

In this paper, ultrasound breast image segmentation is improved by using the volumetric data available in neighboring slices. The new algorithm extends the EM/MPM framework to 3D by including pixels from neighboring frames in the Markov Random Field (MRF) clique. In addition, this paper describes a unique linear cost factor introduced in the optimization loop to compensate for the attenuation common to ultrasound images.

关键词： Bayesian methods Ultrasonic imaging Breast image segmentation Markov random fields Magnetic resonance imaging Acoustic noise image processing Cost function Attenuation

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A recursive shape error concealment algorithm

A recursive shape error concealment algorithm

引用

IEEE International Conference on image processing

作者： Xiaohuan Li A.K. Katsaggelos G.M. Schuster Image and Video Processing Laboratory Department of Electrical and Computer Engineering Northwestern University Evanston IL USA Abteilung Ekktechnik Hochschule für Technik Rapperswil Switzerland

The encoding of shape information is a distinguishing feature of MPEG-4. In error prone communication networks, it is important and efficient to conceal shape errors spatially, so as to avoid propagation of errors in the video frames. The proposed system first defines the missing area's four rectangular neighbors. It then detects in the neighbors the lines that intersect the borders and redefines them in a geometric coordinate system. These lines are paired under some optimization objective so that they connect smoothly in the missing area. Each pair is extrapolated and corrected recursively until a close curve is formed. Test results on various sequences under various error rates are presented and compared with other shape concealment methods.

关键词： Shape computer errors Decoding Streaming media Motion compensation image coding MPEG 4 Standard Laboratories Communication networks Testing

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