Earticle

War State Battle Field is the basement of the military action. Battle Field is very significant for commanders to considerate and make full use of it in decision-making. This is basically depend on the vehicular traffic control in war state battle field. In this the tanks represents a vechicle. A tanks traffic on war state battle field is a vital problem and is seemly a major pretend to conclusion makers. In this research paper we will try to bring the scenario of battle field arena where the traffic consists of the vehicles called tanks. So the main focus in this research is put on the collision detection of the tanks among each other using cloud sensor by controlling the congestion in the battlefield.

The closest iterative point algorithm (ICP) is widely used in medical image registration. But there exist some problems in the following aspects. First, due to its heavily computational load, it has a time-consuming process and a low registration efficiency. Second, due to the fact that it heavily depends on whether the initial rotation and translation matrices of the floating point set can be exactly extracted, it often traps in the local optimum and even fails to register images. In addition, due to the complexity of medical images, it is difficult to automatically extract the salutary feature points. In this paper, by computing the coordinate inertia matrices of the reference and floating images, the rotation angles are obtained and referred to as the initial rotation parameters of ICP for image registration. The edges of the reference and floating images are detected by the edge convolution kernel so-called B-spline gradient operator (BSGO) and then the binarization images involving the feature points are acquired. The experimental results reveal that, this proposed method has a fairly simple implementation, a low computational load, a fast registration and good alignment accuracy. Also, It can efficiently avoid trapping in the local optimum and cater to both mono-modality and multi-modality image registrations.

The color pump noise has been introduced into a two-mode laser system and its effects on the laser system in both homogeneously and inhomogeneously broadened media have been studied. The results show that the correlation time of the color pump noise can make the distribution of the laser intensity concentrate in the region where the laser intensity have larger values, enhance the mean of the laser intensity and stabilize the the system in a homogeneously broadened two-mode laser system; meanwhile, it strengthen the laser intensity of the stronger mode, recedes the laser intensity of the weaker mode and increases the competition between two mode in a inhomogeneously broadened two-mode laser system. Comparatively, it more clear that the influences of the color pump noise on the statistical properties of laser system in inhomogeneously broadened media than that in homogeneously broadened media.

Stemming is a natural language processing task that to remove all derivational affixes from a word. This task proved to be harder for languages with complex morphology such as the Uyghur language. This paper presents a new stemming method for Uyghur words based on CRFs (Conditional Random Fields). In the proposed method all words in the training corpus are segmented into syllables and each syllable are tagged as a part of stem or as a part of affix. We experimentally evaluated this method with five test files each includes 100 sentences , results have shown that our method gets good performance, average stemming precision, recall and F-score in open test reached 98.42%, 98.34% and 98.38% respectively.

With the development of image processing and network technologies, video applications become more and more popular. DiffServ (Differentiated Services) is a suitable architecture to ensure quality of service for simultaneously transmitted video and data streams. In this paper, we evaluate video streaming performance over DiffServ Domain, using myEvalvid extension in ns2. From a comprehensive evaluation, we find that: (1) Employing TSW2CM or other policies with more than one dropping priority is not necessary. (2) Scheduling mode influences the video transmission greatly, especially for parameter weight in WRR or WIRR mode and parameter “maximum consumed bandwidth” in PRI mode. (3) The influence of RED parameters is slight.

On the basis of the traditional structure of noise barrier, this paper seeks aerodynamic load to reduce the variation of maximum surface configuration (porous structure). Using the numerical simulation method, this paper builds a three-dimensional numerical model of deloading type noise barriers and trains. The large fluid calculation software, Fluent, is adopted to conduct simulation calculation of the high-speed deloading noise barriers. This thesis, conducting researches and analysis of the high-speed railway noise barrier aerodynamic load characteristics on the surface, concludes the characteristics of loading surface pressure distribution, time-history features as well as the law of influence factors, which is applicable to deloading sound barrier and lays a theoretical foundation for deloading sound barrier designing.

This paper presents a tri-band rectangular slotted circular micro strip antenna for wideband applications. The antenna operates at 2.96, 6.42 and 7.33 GHz frequency bands for VSWR<1 with an improved impedance bandwidth of 41.23%. The antenna has been designed and simulated on an FR4 substrate with dielectric constant (εr) of 4.4 with an overall size of 50 × 40 × 3.5 mm3. The study of bandwidth improvement is presented in this paper by introducing the slots on surface of circular patch. The measured bandwidths for -10 dB reflection coefficient are 410 MHz (2.80-3.21 GHz) and 3.07 GHz (5.91-8.98 GHz). The simulated results show that the proposed antenna provides good performance in term of return loss and radiation pattern for wideband applications.

Image cropping is a technique to help people improve their taken photos’ quality by discarding unnecessary parts of a photo. A novel method is presented for Image cropping by patches dissimilarities. In this paper, we propose a novel patches dissimilarities algorithm. Firstly, representing the image patches and reducing dimensionality. Then we extract the visual saliency map of these photos based on the patches dissimilarities. Finally, by the saliency map and face priors, we find a cropped region that can be best found. The experimental results demonstrate that our technique is applicable to a wide range of photos and produce more agreeable resulting photos.

This paper presents a novel image segmentation method that performs histogram thresholding based on the conception of Tsallis generalized divergence. Firstly, to fit the image segmentation task, the original formula of Tsallis divergence was simplified, and then the symmetrical version was constructed. After that, the criterion of divergence sum of the objective and background between original and thresholded image was set up based on the symmetrical version of the Tsallis divergence. The optimal threshold obtained by minimizing the criterion of divergence sum. Finally, the proposed method was tested on different gray level images, and the performance was evaluated using uniformity measure, shape measure, and CPU run time. Experimental results indicate the effectiveness of the proposed method.

In this paper, Decision Feedback Equalization (DFE) and Feed forward Equalization (FFE)based on minimum mean square error optimization has been employed to improve the performance of 32 channels, gigabit capacity WDM-PON network. An optical line terminal (OLT) installed at the transmitter end which continuous transmit 32 channels having different colors (wavelengths) of 20GB/s data rate , which is multiplexed by optical multiplexer and transmit through standard single mode fiber (SMF) having length 40km. A link design for 1:64 optical splitters is used as Passive Optical Network (PON) element which creates communication between OLT to different end users. It is observed that FFE and DFE significantly reduce BER by 1.0798e-010, 1.1556e-011, 1.2960e-010 and 8.8979e-009 at four different wavelengths 1550nm, 1559.6nm, 1562.8nm and 1574.8nm by using NRZ (non return zero) modulation format at 20GB/s for 64 users having 40km fiber length respectively. Sharp increase in BER 2.6916e-002, 4.6519e-002, 3.8804e-001 and 5.1570e-002 occurs if data rate increases up to 25 GB/s.

Compressed sensing (CS) provides a new solution for the problems of requiring large amount of measurements data and long data acquisition time in radar application, and both issues also exist in ground penetrating radar (GPR). Aiming at this problem, we adopt impulse radar with CS framework, and transform the GPR imaging into sparse constraint optimization problem performed on time-domain sub-sampling in this paper. Specifically, it focuses on the impulse GPR imaging method based on CS under double underground targets condition containing noise and abundant clutter. Furthermore, the performance of matching reconstruction algorithms under the different signal to noise ratios (SNR), measurement dimensions and sparseness values is also presented. The experimental results show that CS algorithms based on matching reconstruction can obviously reduce measurement data, improve the image quality and make a better anti-noise performance. When SNR of measurement data is 1dB, the probability of accurate imaging can still reach 95%. So we may reasonably conclude that the regularized orthogonal matching pursuit algorithm has a better performance than the other matching algorithms.

For movement target, image recognition with blur is a difficult problem to solve in image acquisition system. The paper proposes an image restoration algorithm based on inverse filtering and wiener filtering. According to original image of movement target by acquisition system, it analyses frequency spectrum characteristic, builds restoration model for image degradation, researches inverse filtering and wiener filtering technologies of image preprocessing algorithm and image restoration algorithm. Further it explains image quality assessment method, discusses objective assessment method without reference in detail. Dealing with the movement target image of actual acquisition, some images are processed based on the restoration method which proved. By contrasting algorithm with result, the restoration method is valid to eliminate blur and noise of disturbing influence from target moving, which proposed combining with inverse filtering and wiener filtering. The result shows that the edge characteristic is obvious and propitious to reflect original target actually.

This paper presents a literature survey on Digital Watermarking within an image. It describes the early work carried out on digital watermarks, including the brief analysis of various watermarking schemes and its applications. This paper also makes a comparison between various watermarking schemes .This paper also gives us a brief introduction about the procedure of digital watermarking.

Dense wavelength division multiplexing (DWDM) is a WDM technology with reduced channel spacing. This technology is really scalable in terms of handling additional wavelengths/users. But the dispersion compensation is a key issue in DWDM at bit rate ≥ 10 Gb/s. Dispersion can be fully compensated by using Dispersion compensating fiber as a compensator. In this paper, the performance of 32 channel DWDM system with post-dispersion compensation using DCF at different bit rates (10, 20 and 40 Gbps) is investigated. The simulation is done in Optisystem simulator. The performance of the simulated system has been investigated in terms of quality (Q) factor and bit error rate (BER).

Power spectral density (PSD) is an effective way to analyze random signals. However, it is a time-consuming calculation when it deals with a rapidly growing massive data by using the serial Matlab circumstances. Though a parallel computing toolbox is involved in Matlab 2004, it is too expensive to be wildly used. According to an algorithm of PSD, a parallel algorithm of cross power spectral density (PACPSD), which was implemented using the Master-Slave parallel programming model with the support of Linux clusters and MPI，was proposed here based on the theory of Welch algorithm. The experiment results reveal that PACPSD can achieve the same accuracy as the function cpsd in Matlab do, and greatly reduce the operation cost.

Nowadays roads are getting overcrowded and the number of vehicles on the roads is increasing. The main reason is the increase in the population of metro cities, urbanization, and economical development of the country that subsequently led to the increased demand for vehicular travel. Incident detection and Traffic congestion are the serious issues in Traffic engineering applications and Intelligent Transport System. Hence the aim of the proposed system is to build an automatic traffic monitoring system which can replace or reduce manual traffic monitoring. The proposed mathematical Morphogical technique is able to detect and track the moving vehicle from the traffic video in real time and give a message to the traffic control station. The experimental results show that the proposed technique can be adopted under various traffic patterns, weather conditions and illuminations.

This paper investigates the problem of image restoration when the image is corrupted by Pepper-and-salt noise and proposes a new restoration algorithm based on quadtree data structures. The crucial parts of the algorithm are picking noise and fuzzy estimation, so that unlike some other usual denoising methods, it avoids blurring and averaging edges and non-noise pixels. This paper describes, analyzes and compares several methods and results of removing noise from image. Experimental results indicate that the new algorithm proposed by this paper is superior.

Due to memory limitation, the displaying and processing of the oversized images have been a bottleneck for various applications, which is a hot research spot in the image processing field. The traditional methods are almost based on the BMP format to generate oversized images, of which the time and space complexity are very high. In this paper, we have deeply analyzed the encoding scheme of JPEG image and proposed an oversized image generation method based on stitching JPEG file streams. According to this method, the oversized images are block plotted and then transformed and saved as JPEG format files respectively. In the end, the block JPEG files are then combined into an integrated JPEG image. The experiment results show that, our method can effectively improve the speed of oversized image generation and reduce the memory consumption. The time and space performance of our method are better than existing methods.

Scheduling messages on the controller area network (CAN) corresponds to assigning identifiers (ID’s) to messages according to their priorities. This paper presents a technique of dynamic scheduling in cars using CAN architecture. Static scheduling Id allocation method has several problems like delay, starvation and less accuracy. To overcome these problems the Dynamic approach of message id allocation from message id window is proposed in this paper, which increases the randomness and decreases the biasness by dynamically changing priorities in a CAN network. CAN based architecture is presented and design is implemented using Xilinx device.

In this paper, a novel silicon micro-machined gyroscope is introduced, which is driven by the rotating carrier’s angular velocity. The principle of structure is analyzed .The mathematic module is also established and the dynamics parameters of the gyroscope is calculated, Design and analysis of signal processing circuit, design and processing of the gyroscope sensing head, at last, the gyroscope is tested, the test results and the theoretical analysis is consistent。

This paper presents a kind of coverage optimization strategy based on improved artificial fish swarm algorithm for wireless sensor networks, by adaptively adjusting the vision range and the step length of artificial fish swarm the accuracy of optimization, convergence speed and stability are improved, then combining with the performance of WSN network coverage, the network coverage can be optimized. The simulation results show that comparing to the basic artificial fish swarm algorithm, the network coverage ratio of improved artificial fish swarm algorithm improves 17%.

The aim of this work is signal processing of Secondary Ions Mass Spectrometry (SIMS) profiles for improving the depth resolution beyond its physical and instrumental limits. Indeed, we propose a new iterative deconvolution algorithm based on Tikhonov-Miller regularization where a priori model of solution is included. The latter is a denoisy and pre-deconvoluted signal obtained by wavelets shrinkage algorithm. It is shown that this new algorithm gives best results without artifacts and oscillations related to noise. This leads to a significant improvement of the depth resolution and peaks’ maximums. The SIMS profiles are obtained by analysis of delta layers of boron in a silicon matrix using Cameca-Ims6f instrument at oblique incidence. In the light of the obtained results, the advantages and limitations of this new method as well as suggestions for future work are presented and discussed.

It has been found that poor quality images decrease the performance of finger vein recognition system, due to missing, vague or spurious features. Therefore, it is important for a finger vein recognition system to evaluate the quality of finger vein images. In this paper, a new method based on Support Vector Regression (SVR) is proposed for finger vein image quality evaluation. In our method, we first manually annotate quality scores for finger vein images in training set and extract five quality features of these images. Then quality scores and quality features are used to build a SVR model, which will be applied to evaluate quality for testing images. In addition, we explore the use of quality score and ascertain that quality score can be used as ancillary information to enhance recognition accuracy for finger vein. Experimental results show that our proposed method is effective for finger vein image quality evaluation.

In this paper, two different types of robot head shaped patch antennas are proposed and a comparative study is presented. Both the proposed antennas have same dimensions except at the mouth position. These antennas are fed by coaxial feeding technique and are etched on an FR-4 substrate with relative permittivity 4.4. The proposed antennas produce multiple bands resonating at 1.63 GHz, 5 GHz, 6.13 GHz, 6.91 GHz and 9.5 GHz frequencies with excellent return loss characteristics. These frequencies have applications in wireless, satellite, radar and mobile communications.

A novel framework for highly dynamic scene segmentation through foreground hypothesis is developed here. This framework enables robust foreground segmentation by ranking object hypothesis over spatial space to achieve consistent object candidates and binary segmentation of a video sequence. Inside object candidates derived from spatial features in each frame are first estimated. This is followed by ranking the object candidates over a specific hypothesis space so as to yield consistent and dense object proposals. An efficient higher-order graph-cut method is adapted to optimize a Markov Random Field (MRF) model, which is instantiated by the estimated foreground hypothesis with highest score. We demonstrate the performance of our approach through experimental evaluation on a typical dynamic scene benchmark from Freiburg-Berkeley Motion Segmentation Dataset. Compared with a state-of-the-art algorithm, our method achieves improved and robust segmentation performance when dealing with highly dynamic image sequences. The segmentation accuracy of the proposed method improved by 10.19% and 92.66% pixels are correctly classified.

Feature extraction methods of image directly affect the feature recognition results based on computer vision-based gesture recognition. This paper proposed a gesture feature extraction method of hexagonal structure, which is based on histograms of oriented gradients. This paper transforms the quadrilateral structure into hexagonal structure of the image and defines hexagonal block structure. Using different structures, different sizes of hexagonal blocks extract gesture feature and recognize on different sizes image. Experimental results show that hexagonal structure block is more appropriate than conventional histograms of oriented gradients structure block, the hexagonal structure histograms of oriented gradients feature extraction method is more efficient than the square and circular structure histograms of oriented gradients feature, using gentle_adaboost classifier achieved higher recognition rate.

Color Image enhancement is a process in which the perceptual information of an image is improved to obtain more information and details contained in the image. It improves the subjective quality of an image by working with original data. This paper focuses on evaluating the performance of various image enhancement techniques. These techniques are either based on histogram modification or are based on fuzzy logic. The techniques are compared using two quantitative measures namely; Contrast Improvement index (CII) and Tenengrad measure. The results have shown that Lab and edge preservation based fuzzy image enhancement (LEFM) yields the best results.

Most of the existing fingerprint retrieval systems are based on the overall characteristics and detailed features of fingerprints, and their performance is poor in the cases of low-quality fingerprint images, such as incomplete fingerprint images. In order to improve the recognition speed, accuracy, and robustness of automated fingerprint recognition systems based on large-scale fingerprint databases, in this paper, we propose a fast fingerprint classification retrieval and identification method based on Scale Invariant Feature Transform (SIFT) and Local Sensitive Hash (LSH) algorithms. A method based on scale space theory extracts SIFT feature point descriptors of relatively high-quality fingerprint images in accordance with the principle of a greater matching contribution rate, uses multi-template image feature fusion technology to build a stable fingerprint feature template database, achieves the storage and retrieval of high-dimensional SIFT features using the LSH algorithm, and carries out matching progressively by level on the basis of SIFT’s matching principle of close neighboring priority scale. Experimental results show that the proposed method has strong penetration, high retrieval efficiency, good recognition accuracy, and strong robustness, thereby providing a fast and efficient retrieval and matching mechanism for the automated recognition of the large-scale fingerprint database, with strong practicality.

In recent years, the theory of partial differential equations (PDE) for its rigorous mathematical theory foundation has been widely used in the fields of image processing. Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. In order to detect the noise in the medical images, many models are studied, but the noises in medical images are much more complex than typical images. This paper introduces a new image noise detection approach using morphology and partial differential equations where are based on the morphology reconstruction with anisotropic diffusion to make full use of the advantage of Catte model. This proposed approach has been tested with the biomedical cell images with comparing with the Catte model, PM model and Canny model. The experimental results show that this proposed approach outperforms the other three models in terms of defined indicator and efficiency.