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Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies include both work flow errors and low performance problems. People often use system logs produced by distributed systems for troubleshooting and problem diagnosis. However, manually inspecting system logs to detect anomalies is unfeasible...
A key frame extraction algorithm based on sub-shot segmentation and entropy computing is proposed. Firstly the reconstructed matrix of each frame in shots is computed through sub-space projection. Secondly sub-shot segmentation is processed according to the difference of singular value between frame and its reconstructed matrix, as well as difference of histogram feature between frame and mean value...
A mechanism involving evolutionary genetic programming (GP) and the expectation maximization algorithm (EM) is proposed to generate feature functions automatically, based on the primitive features, for an image pattern recognition system on the diagnosis of the disease OPMD. Prior to the feature function generation, we introduce a novel technique of the primitive texture feature extraction, which...
This paper introduces a novel method to detect the typical LSB (Least Significant Bit) embedding and the LSB matching steganography methods applied to grayscale images. The proposed method determines the changes made to some selected features extracted from the gray level run length matrix. It is shown that the run length characteristics can significantly be affected by the embedded message bits,...
This paper presents novel algorithms for shot boundary detection and key frames extraction. The algorithm differs from conventional methods mainly in the use of image segmentation and attention model. Matching difference between two consecutive frames is computed with different weights. Shot boundaries are detected with automatic threshold. Key frame is extracted by using reference frame-based approach...
The mean-shift algorithm has been proved to be efficient for object tracking. Traditional mean-shift algorithm uses global color histogram features, regardless the features belong to the object or to the background, which will cause localization drift. In this paper, we propose a new algorithm which can overcome this disadvantage. Our hypothesis is that the features that best discriminate between...
In this paper we discuss the application of 3D scene reconstruction techniques in the area of automatic semantic annotation, search and retrieval of unedited video footage. Rather than working with static key-frames we exploit the time-depended dynamic properties of a moving camera. Based on state of the art camera self calibration techniques we develop a powerful analysis chain. We demonstrate, that...
Text extraction is a very important step in text understanding. Natural scene images bring new challenges to correctly extract interested text regions. In the paper, an efficient and low-complexity text extraction method is used to extract Korean text from signboards of shops. By combining the edge-based approach and some knowledge of the Korean text specified in our application, our method successfully...
The extraction of playing shots is helpful for video analysis. In this paper, we propose an algorithm: first, the shots are segmented by detecting the shot boundaries (both abrupt cuts and gradual transitions), and wipes are discarded directly; then from the rest shots, playing shots are extracted by shot classification. Experimental results confirm the efficiency of our proposed algorithm.
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