A distributed warehouse management system is design based on the *** framework. Unlike many frameworks which focus on the database data operation or construct flexible user interface, the proposed project mainly focus...
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Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside on different manifolds of possible dif...
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Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize th...
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Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.
This paper presents a copy-paste block detection method based on characteristics of double JPEG compress. The JPEG compress will bring JPEG compression characteristics to the DCT coefficients, these characteristics ar...
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This paper presents a copy-paste block detection method based on characteristics of double JPEG compress. The JPEG compress will bring JPEG compression characteristics to the DCT coefficients, these characteristics are closely related with the quality factor. Copy-paste tamper between JPEG images will disrupt the JPEG compression characteristics of the final image. The method in this paper is designed to deal with double JPEG compression whose DCT blocks are different during the two compresses, and the experiment shows that our method can work effectively on double JPEG compression with different quality factors and is not subject to the impact of DCT blocks.
In order to protect the copyright of the image, in this paper proposed a novel important sub-tree (Istree) digital watermarking algorithm based on contourlet transform. First, Shuffling is applied by watermarking imag...
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This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state t...
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This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update *** the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model ***,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking *** are three main ***,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy ***,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle ***,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and *** performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.
A new algorithm, Laplacian MinMax Discriminant Projection (LMMDP), is proposed in this paper for supervised dimensionality reduction. LMMDP aims at learning a discriminant linear transformation. Specifically, we defin...
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An effective dual-channel noise reduction algorithm is proposed based on sparse representations. The algorithm is composed of the following steps. Firstly, overlapping patches sampled from two channels together instea...
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An effective dual-channel noise reduction algorithm is proposed based on sparse representations. The algorithm is composed of the following steps. Firstly, overlapping patches sampled from two channels together instead of each channel one by one are trained to be a dictionary via K-SVD. Secondly, OMP(Orthogonal-Matching-Pursuit) reconstruction algorithm is applied to obtain the sparse coefficients of patches using the dictionary. Thirdly, the denoising speech can be obtained by the updated coefficients. Lastly, the above three steps are iterated to get clearer speech until some conditions are reached. Experimental results show that this algorithm performs better than that with single channel.
Thousands of fragments of ceramics (called sherds for short) are found at archaeological excavation sites. One of these excavations sites is Tel Dor in Israel. The excavators in Dor use hand drawings and a profilograp...
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Thousands of fragments of ceramics (called sherds for short) are found at archaeological excavation sites. One of these excavations sites is Tel Dor in Israel. The excavators in Dor use hand drawings and a profilograph for documentation of sherds. Both techniques acquire a cross-section of the sherd, the so called profile line, which is used for classification and statistical analysis about the ancient population of Dor. As proposed in previous work we are developing a fully automated system for documentation of sherds by 3D-acquisition based on structured light and extraction of the profile line. Consequently we joined the field trip to Tel Dor in July, 2004 to compare in-situ the accuracy and performance of the traditional hand drawings, the profilograph and our system. We therefore alos measured the time for each step of documentation in-situ to find bottle-necks in documented sherds per hour. Based on these results we could propose an improvement to increase the throughput of our system by a factor of 5. The results of the comparison of all three techniques of documentation of sherds, the improvement for our system and a methodological experiment for future work are shown in this report.
This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software o...
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This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.
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