The paper proposes a novel technique for robust changedetection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between grad...
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ISBN:
(纸本)0769512720
The paper proposes a novel technique for robust changedetection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between gradient vectors is described. The robustness of the measure with respect to noise and illumination changes has been analyzed. Two ways to integrate the intensity and texture differences are proposed. The first combines two measures according to the weightage of texture evidence, while the second takes into additional constraint of smoothness. The parameters of the algorithm are selected automatically. The computational complexity analysis indicates that the proposed technique can run in real-time. Experimental results show that by exploiting both intensity and texture differences for changedetection, one can obtain much better segmentation results than using the intensity or structure difference alone.
We propose an optimization of a computer based changedetection technique based on Iterative Principal Component Analysis (IPCA). We determine and evaluate the changes between an airborne and a spaceborne multispectra...
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We propose an optimization of a computer based changedetection technique based on Iterative Principal Component Analysis (IPCA). We determine and evaluate the changes between an airborne and a spaceborne multispectral image data set, the latter recorded by the commercial satellite IKONOS-2. The changedetection algorithm proved to be applicable to large remotely sensed data sets. A vegetation filter, a shadow filter and an oversaturation filter improved the accuracy of the results. When applying all filters more than 80 percent of the objects with changes due to construction activity are detected by the IPCA algorithm. The false alarm rate (change of an object indicated but not verified) is about 5 percent.
The data at many Web sites is changing rapidly, and a significant amount of this data is presented in HTML documents that consist of markups and data contents. Although XML is becoming more popular for data exchange, ...
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ISBN:
(纸本)0769510019
The data at many Web sites is changing rapidly, and a significant amount of this data is presented in HTML documents that consist of markups and data contents. Although XML is becoming more popular for data exchange, the presentation of data contained in XML documents is given, by and large, in the HTML format using XSL(T). Since HTML was designed to "display" data from the human perspective, it is not trivial for a machine to detect (hierarchical) changes of data in an HTML document. In this paper, we propose a heuristic algorithm, called SCD (Semantic changedetection), to detect semantic changes to the hierarchical data contents in any two HTML documents automatically. Semantic changes differ from syntactic changes since the latter refer to changes of data contents with respect to markup structures according to the HTML grammar. SCD does not require pre-processing, nor any knowledge of the internal structure of the source documents beforehand. The time complexity of SCD is O[(|X|/spl times/|Y|)log(|X|/spl times/|Y|)], where |X| and |Y| are the number of unique branches in the syntactic hierarchies of any two given HTML documents, respectively.
In this paper we present a new algorithm to detect abrupt changes in a signal when there is no a priori knowledge of the hypotheses on the process to be detected. This algorithm is based on the CUSUM algorithm. It can...
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In this paper we present a new algorithm to detect abrupt changes in a signal when there is no a priori knowledge of the hypotheses on the process to be detected. This algorithm is based on the CUSUM algorithm. It can be applied in case of frequency and energy changes. This algorithm works when the samples are dependent and autoregressive modeling is needed. It is used to distinguish EMG segments from noise segments.
We have undertaken mapping of the ice sheet margin and grounding zone in East Antarctica using Landsat TM and ERS SAR images in order to establish an accurate baseline for the detection of future change. As part of th...
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We have undertaken mapping of the ice sheet margin and grounding zone in East Antarctica using Landsat TM and ERS SAR images in order to establish an accurate baseline for the detection of future change. As part of this work we have implemented a computer-aided edge-following algorithm to provide an objective and consistent mechanism for analysis of different images. Accurate geocoding of the images is achieved with sparsely distributed ground control points and a transformation of the images which preserves their inherent geometric properties and internal positioning accuracy. An initial comparison with published maps has identified significant changes in several large ice shelves.
We propose a video segmentation method using a histogram-based fuzzy c-means (HBFCM) clustering algorithm. This algorithm is a hybrid of two approaches and is composed of three phases: the feature extraction phase, th...
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ISBN:
(纸本)078037293X
We propose a video segmentation method using a histogram-based fuzzy c-means (HBFCM) clustering algorithm. This algorithm is a hybrid of two approaches and is composed of three phases: the feature extraction phase, the clustering phase, and the key-frame selection phase. In the first phase, differences between color histogram are extracted as features. In the second phase, the fuzzy c-means (FCM) is used to group features into three clusters: the shot change (SC) cluster, the suspected shot change (SSC) cluster, and the no shot change (NSC) cluster. In the last phase, shot change frames are identified from the SC and the SSC, and then used to segment video sequences into shots. Finally, key frames are selected from each shot. Simulation results indicate that the HBFCM clustering algorithm is robust and applicable to various types of video sequences.
A recursive least squares (RLS) algorithm with selective modification of the system estimation covariance matrix is employed to track the rapidly changing components of system parameters. A new on-line wavelet detecto...
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A recursive least squares (RLS) algorithm with selective modification of the system estimation covariance matrix is employed to track the rapidly changing components of system parameters. A new on-line wavelet detector is designed for accurately identifying the changing locations and the branches of changing parameters. Employing theses techniques, the tracking performance of the proposed algorithm to rapidly changing systems can be significantly improved.
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