This paper presented an improved linear discriminant analysis (LDA) algorithm for face recognition, which can effectively deal with the two problems in traditional LDA-based approaches: (1) the small sample size probl...
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This paper presented an improved linear discriminant analysis (LDA) algorithm for face recognition, which can effectively deal with the two problems in traditional LDA-based approaches: (1) the small sample size problem, and (2) the Fisher criterion is nonoptimal with respect to classification rate. In particular, the proposed algorithm can also improve the classification rate of one or several appointed classes. The key to this method is to use the technique that it can reserves the significant discriminatory information for dimension reduction and meanwhile utilize a modified Fisher criterion. The comparative experiments on ORL face database verify the effectiveness of the proposed method.
A novel dominant correlogram based particle filter was proposed for an object tracking in visual surveillance. Particle filter outperforms the Kalman filter in non-linear and non-Gaussian estimation problem. This pape...
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A novel dominant correlogram based particle filter was proposed for an object tracking in visual surveillance. Particle filter outperforms the Kalman filter in non-linear and non-Gaussian estimation problem. This paper proposed incorporating spatial information into visual feature, and yields a reliable likelihood description of the observation and prediction. A similarity-ratio is defined to evaluate the effectivity of different similarity measurements in weighing samples. The experimental results demonstrate the effective and robust performance compared with the histogram based tracking in traffic scenes.
This paper investigated the performances of a well-known car-following model with numerical simulations in describing the deceleration process induced by the motion of a leading car. A leading car with a pre-specified...
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This paper investigated the performances of a well-known car-following model with numerical simulations in describing the deceleration process induced by the motion of a leading car. A leading car with a pre-specified speed profile was used to test the above model. The results show that this model is to some extent deficient in performing the process aforementioned. Modifications of the model to overcome these deficiencies were demonstrated and a modified car-following model was proposed accordingly. Furthermore, the delay time of car motion of the new model were studied.
The aim of modulation classification (MC) is to identify the modulation type of a communication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-ba...
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The aim of modulation classification (MC) is to identify the modulation type of a communication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their reccgnition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis (PCA) with different transformation inputs,can achieve satisfactory accuracy even at low SNR (as low as 2 dB). Due to the properties of spectrogram, the statistical patternrecognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.
A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decis...
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A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarchal block-matching based on these ***, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.
In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysalis's line-based wavelet transformation coding. There was not image tiling ...
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In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysalis's line-based wavelet transformation coding. There was not image tiling in the algorithm. The supposed algorithm modeled with contexts for different subband after quantifying wavelet coefficients uniformly. A modified Golomb-Rice algorithm with low complexity was adopted as entropy coder. The experiment shows that the memory requirement of the algorithm is far less than that of the SPIHT in compressing images with huge size. The complexity of the entropy coding of the algorithm is reduced largely. The algorithm is especially appropriate for remote sensing image compression system with power and space limited.
Two treatments of color image segmentation with information entropy were introduced: (1) The layers of the image are analyzed with whole information entropy and the segmentation resolution can be self-adapted;(2) The ...
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Two treatments of color image segmentation with information entropy were introduced: (1) The layers of the image are analyzed with whole information entropy and the segmentation resolution can be self-adapted;(2) The image is segmented with patch information entropy by segmenting the image in patch. According to the segmentation results, it can be found that the image segmentation with alterable resolution is more similar to the processing character of human vision.
A regularized restoration algorithm based on maximum-likelihood estimation was presented for restoring object images from the noisy turbulence-degraded images. The logarithmic maximum-likelihood function for multi-fra...
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A regularized restoration algorithm based on maximum-likelihood estimation was presented for restoring object images from the noisy turbulence-degraded images. The logarithmic maximum-likelihood function for multi-frame image data based on the model of image random field was built, and some auxiliary terms to smooth noise while preserve the edges of images and the penalized item to avoid trivial solutions were added to the maximum-likelihood function. The iterative formulas of calculating the PSFs and object image were derived so that the PSFs and the object image could be estimated in the iterative manner. A parallel processing scheme for the algorithm is also proposed. The restoration experiments on the simulated turbulence-degraded images in the case of noise show that the proposed algorithm has high ability of noise-resisting and it has some practical applications.
Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation k...
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Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation kernel functions belong to Walsh ordering Walsh function system. We worked out a recursive property of the matrix WHKRm+1 corresponding to the first KR m+1 Walsh-Haar functions in Walsh-Haar function system, and we also proved that Walsh-Haar function system is perfect and orthogonal similar to Walsh function system and Haar function system. Thus, discrete Walsh-Haar transformation (DW-HT) is an orthogonal transformation that can be widely used in signal processing. In this paper, using the recursive property of the matrix WHKRm+1 and the fast algorithm of discrete Walsh transformation (DWT) in Walsh ordering, we have designed a fast algorithm of Walsh ordering DW-HT based on the bisection technique. The idea and method used in this paper can be used for designing fast algorithms of other ordering DW-HTs and other discrete orthogonal transformations.
Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection...
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Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection of infrared weak targets based on multifeature distance map (MFDM) in image sequences is proposed. As for small weak targets, there are many features, such as local entropy, average gradient strength. These features depict the characteristics of small infrared targets and can be extracted. Multifeature-based fusion techniques are applied to detect such weak targets. The problem of detecting small targets is converted to search peak values in specified feature space where multifeature vectors space (MFVS) is considered. Distance map (DM) can be derived according to feature vectors and target detection is performed in DM. In order to accumulate energy of targets deeply and suppress background and clutters to a great extent, five distance maps obtained by corresponding five consecutive frames are utilized to fuse with average weight, which results in the fact that the contrast between targets and background including clutters are enlarged and that the feature peaks of targets are obvious different from background and clutters. After these steps, a contrast segmentation method is used to extract targets from complicated background on the fused DM. Actual infrared image sequences in background of sea and sky are applied to validate the proposed approach. Experimental results demonstrate the robustness of the proposed method with high performance.
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