Score: 33
Uploads: 98
Downloads: 4495
Create time: 2013-11-23 21:32:12

Upload log: - Convolution neural networks are inherently limited to model geometric transformations due to the fixed geometric structures in their building modules. - A simple yet effective object descriptor for visual tracking is proposed in this paper. We first decompose the bounding box of a target object into multiple patches - Discriminative Correlation Filter based methods have significantly advanced the state-of-theart in tracking. - Yet because these graph constructions are complex and highly specific to a particular energy function, graph cuts have seen limited application to date. In this paper we give a characterization of the energy functions
Intatijects - In this paper, we propose a new model for active contours to detect objects in a given image - Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic segmentation
Segmentation As Selective Search.rar - This paper addresses the problem of generating possible object lo- cationsforuseinobjectrecognition. WeintroduceSelectiveSearch which combines the strength of both an exhaustive search and seg- mentation - The active contour models have been popularly employed for image segmentation for almost a decade now. Among the se active contour models,the level set based Chan and Vese algorithm is a popula rregion-based model - Image segmentation is one of the earliest and most important stages of image processing and plays an important role in both qualitative and quantitative analysis of medical ultrasound images but ultrasound images have low level of contrast and are corrupted with strong speckle noise. - This paper presents a novel technique of image classification using BOVW model. The entire process first involves feature detection of images using FAST - There are both multiple-scale and single scale exposure fusion schemes. Three quality measures of proper exposure, good contrast, and high saturation were used to determine how much a given pixel will contribute to the final synthesized image - Multi-exposure image fusion is considered an effective quality enhancement technique widely adopted in consumer electronics, but little work has been dedicated to the perceptual quality assessment of multi-exposure fused images.In this paper, we first build an MEF database and carry - If a neuron receives a stimulus in its resting state its membrane potential is mainly charged by the stimulus directly At the same time - This paper presents a novel yet intuitive approach to unsupervised feature learning. Inspired by the human visual - Fuzzy clustering algorithms like the popular fuzzy c-means algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules. When the fuzzy clusters are used to derive membership functions for a fuzzy rule-based system,then the corresponding fuzzy sets should fulfill some requirements like boundedness of support or unimodality. - In this paper, we present an efficient method for nonnegative matrix factorization based on the alternating nonnegative least squares framework. Our approach adopts a monotone projected Barzilai–Borwein (MPBB) method as an essential subroutine where the step length is determined without line search. - Assume that we look through the moving water surface and observe an underwater object (for example, a coral reef - Image forgery is becoming a growing threat to information credibility. Among all kinds of image forgeries,photographic composites of human faces have very serious impacts - The question of how our perceptions derive from sensory - Tiffs paper presents a new operator called entropy operator for extracting edges using entropy of brightness in a local region of a picture. This operator calculates the entropy of brightness in the region. The entropy
Tper - This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD) with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances. Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation - this paper introduced the image preprocessing and proposed a novel method of blind image deblurring - Image segmentation is an important processing in many applications such as image retrieval and computer vision. One of the most successful models for image segmentation is the level set methods which are based on local context. The methods, though comparatively effective in segmenting images with inhomogeneous intensity, are considerably computation-intensive - This paper describes the theory and algorithms of distance transform for fuzzy subsets, called fuzzy distance transform
Differitative .zip - watershed algorithm. - medical image segementation - Segmentation of the cone-beam computed topographic (CBCT) image is an essential step for generating three- dimensional (3D) models in the diagnosis and treatment plan- ning of the patients - The uation of ventricular function is impor- tant for the diagnosis of cardiovascular diseases. It typically involves measurement of the left ventricular (LV) mass and LV cavity volume. Manual delineation of the myocardial contours is time-consuming and dependent on the subjective experience of the expert observer. In this paper, a multi-atlas method is proposed for cardiac magnetic resonance (MR) image segmentation. The proposed method is novel in two aspects - In magnetic resonance (MR) imaging, image spatial resolution is determined by various instrumental limitations and physical considerations. This paper presents a new algorithm for producing a high- resolution version of a low-resolution MR image. The proposed method consists of two consecutive steps: (1) reconstructs a high-resolution M - In this paper, we propose a multi-sensor super-resolution framework for hybrid imaging to super-resolve data one modality by taking advantage of additional guidance images of a complementary modality. This concept is applied to hybrid 3-D range imaging in image-guided surgery, where high-quality photomet- ric data is exploited to enhance range images of low spatial resolution. We formulate super-resolution based on the maximum a-posteriori (MAP) principle a - er than mean squared error (MSE) function only. As an additional merit, it is also revealed that rigorous Mercer kernel condition is not required in FKNN networks. When the proposed architecture of FKNN networks is constructed in a layer-by-layer way, i.e., the number of the hidden nodes of every hidden layer may be determined only in terms of the extracted principal com- ponents after the explicit execution of a KPCA, we can develop FKNN’s deep architecture such that its deep learning framework (DLF) has strong theoretical guarantee. Our experimental results about image classification manifest that the proposed FKNN’s deep architecture and its DLF based learning indeed enhance the classification performance - Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a pulse coupled neural network method to merge images different sensors, in order to enhance visualization for surveillance. On the basis of standard mathematical model of pulse coupled neural network, a novel step function is adopted to generate pulses. Subjective and objective image fusion performance measures are introduced to assess the performance of image fusion schemes. Experimental results show that the image fusion method using pulse coupled neural network is effective to merge images different sensor - Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron can capture its adjacent neurons to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a very good mechanism for image filtering when the image is damaged with pep and salt (PAS) type noise. An adaptive filtering method, in which the noisy pixels are first located and then filtered based on the output of the PCNN, is presented. The threshold function of a neuron in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise contaminated image respectively. The filtered image has no distortion for noisy pixels and only less mistiness for non-noisy pixels, compared with the conventional window-based filtering method. Excellent experimental results show great effectiveness and efficiency of the proposed method, especially for heavy-noise contaminated images - Image matting is the extraction of a foreground object from an image and determination of the transparency of each pix- el. Matting is inherently an ill-posed and underconstrained problem. Therefore, some assumptions need to be made to solve it. Recent methods that provide a closed-form solution to this problem are based on the assumption of either local smoothness or the nonlocal principle, but they cannot always produce satisfactory matting results. In this paper, we pro- pose a K-nearest neighbors (KNN)-based color line model that combines and preserves the advantages of both the above assumptions. The experimental matting results indicate that they are of comparable or higher quality than those obtained by the existing methods based on the above two assumptions. - resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio-frequency coils or to problems associated with the acquisition sequences. The result is a slowly varying shading artifact over the image that can produce errors with conventional intensity- based classification. Our algorithm is formulated by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to compensate for such inhomogeneities and to allow the labeling of a pixel (voxel) to be influenced by the labels in its immediate neighborhood. The neighborhood effect acts as a regularizer and biases the solution toward piecewise-homogeneous labelings. Such a regularization is useful in segmenti - The food security problems which occurred more and more in recent years seriously influenced people’s normal life. Government and some castes increased their supervision ability gradually about the food security problems and some related law and rule were established. Food impurity is one of the food security problems. Manufacture enterprises cry for a quickly and non-destructive detective equipment to check their packaged food. But at present the equipment is depended on import. This paper researched the market background and united the requirement of an important big project of Shanghai agriculture government, which is the research of X-ray food impurity detective equipment. In this paper, the author researched the key technologies and developed X-ray non-destructive detective equipment, which has an independence knowledge property right. - we present a nonlinear version of the well-known anomaly detection method referred to as the RX-algorithm. Extending this algorithm to a feature space associated with the original input space via a certain nonlinear mapping function can provide a nonlinear version of the RX-algorithm. This nonlinear RX-algorithm, referred to as the kernel RX-algorithm, is basically intractable mainly due to the high dimensionality of the feature space produced by the nonlinear mapping function. However, in this paper it is shown that the kernel RX-algorithm can easily be implemented by kernelizing the RX-algorithm - Abstract—Wear Particle Analysis, as an effective method in mechanical equipment condition monitoring, has been widely and successfully applied to many fields, i.e. weapon equipment, maintenance and daily management. To avoid the influences such as complexity of tribo-system, scrambling and randomicity of the wear particle, an image analysis technique based on Riesz - Multispectral remotely sensing imagery with high spatial resolution, such as QuickBird, IKONOS satellite imagery or Aerial imagery, especially in urban scenes, often perform spectral variations and rich details within a category, resulting in a poor accuracy of classification. To seek an efficient solution, this paper presents a non-parametric and variational multiple level set model by a joint use of Aerial image and two products, digital terrain model (DTM) and digital surface model (DSM), directly or indirectly derived raw LiDAR (Light Detection And Ranging) 3D point cloud data. Proposed model is to minimize an energy function. The energy includes two terms. First term is mainly image-based energy which introduces Parzen Window density estimation technique in the multiple level set framework. To make up the disadvantages - liver contrast-enhanced CT images that uses shape-intensity prior level set combining probabilistic atlas and probability map constrains. We first weight all of the atlases in the selected training datasets by calculating the similarities between the atlases and the test dataset to dynamically generate a subject-specific probabilistic atlas for the test dataset. Based on the generated probabilistic atlas - image analysis, since thickening of the bladder wall can indicate abnormality. However, it is a challenging task due to the artifacts inside bladder lumen, weak boundaries in the apex and base areas, and complicated outside intensity distributions. To deal with these difficulties, in this paper, an adaptive shape prior constrained directional level set model is proposed to segment the inner and outer boundaries of the bladder wall. In addition, a coupled directional level set model is presented to refine the segmentation by exploiting the prior knowledge of region information and minimum thickness. With our proposed method, the influence of the artifacts in the bladder lumen and the complicated outside tissues surrounding the bladder can be appreciably reduced - Image segmentation is among the most studied problems in image understanding and computer vision. The goal of image segmentation is to partition the image plane into a set of meaningful regions. Here meaningful typically refers to a semantic partitioning where the computed regions correspond to individual objects in the observed scene. Unfortunately, generic purely low-level segmentation algorithms often do not provide the desired segmentation results, because the traditional low level assumptions like intensity or texture homogeneity and strong edge contrast are not sufficient to separate objects in a scene. - This paperproposesanoptimumdesignmethodfortwo-dimensionalheatconductionproblemwith heat transferboundaryconditionbasedontheboundaryelementmethod(BEM)andthetopology optimization method.Thelevelsetmethodisusedtorepresentthestructuralboundariesandthe boundary meshisgeneratedbasedoniso-surfaceofthelevelsetfunction.Amajornovelaspectofthis paper isthatthegoverningequationissolvedwithoutersatzmaterialapproachandapproximatedheat convectionboundaryconditionbyusingthemeshgeneration.Additionally,theobjectivefunctionalis defined alsoonthedesignboundaries.First,thetopologyoptimizationmethodandthelevelsetmethod are briefly discussed.Usingthelevelsetbasedboundaryexpression,thetopologyoptimizationproblem for theheattransferproblemwithheattransferboundaryconditionisformulated.Next,thetopological derivativeoftheobjectivefunctionalisderived.Finally,severalnumericalexamplesareprovidedto confirm th idityofthederivedtopologicalderivativeandtheproposedoptimumdesignmethod - Since most current scene understanding approaches operate either on the 2D image or using a surface-based representation, they do not allow reasoning about the physical constraints within the 3D scene. Inspired by the “Blocks World” work in the 1960’s, we present a qual- itative physical representation of an outdoor scene where objects have volume and mass, and relationships describe 3D structure and mechani- cal configurations. Our representation allows us to apply powerful global geometric constraints between 3D volumes as well as the laws of statics in a qualitative manner - Diffuse objects generally tell us little about the surround- ing lighting, since the radiance they reflect blurs together incident lighting many directions. In this paper we discuss how occlusion geometry can help invert diffuse reflectance to recover lighting or surface albedo. Self- occlusion in the scene can be regarded as a form of coding, creating high frequencies that improve the conditioning of diffuse light transport. Our analysis builds on a basic obser- vation that diffuse reflectors with sufficiently detailed geome- try can fully resolve the incident lighting - The component pick-and-place sequence is one of the key factors to affect the working efficiency of theShuffled Frog-leaping Algorithms - Due to the lack of local searching mechanism, the solution accuracy of kineticmolecular theory optimization algorithm needs to be improved. And the misguidance may occur when the current optimal values is a local extremum. In view of the important role of elites in the optimization process, we improved the algorthm based on co-evolution and elite strategy, and then proposed a M elite synergy kineticmolecular - Complex and hyper-complex valued filtering play a substantial role in signal processing, especially to obtain local features in the frequency and phase domain - We propose a new class of models for image restoration and decomposition by functional minimization. Following ideas of Y. Meyer in a total variation minimization framework of L. Rudin, S. Osher, and E. Fatemi, our model - This paper analysed the kernel of embedded real-time operating system ARTs-OS. And then we discussed the framework of network system and its way of work. From the basic functions ARTs-OS micro-kernel provides, we developed the basic strategy to achieve TCPIP protocol stack according to the way of the process of network services, provide the network communication function outside the core To run multiple threads in network services process and distribute the module to a number of threads to achieve the final function Using the way of message loop to receive service requests the application - TCP Reno is widely deployed in networks all of the world,and is considered to be the standard protocol of TCP congestion control algorithm.It consists of four mechanisms:Slow Start,Congestion Avoidance,Fast Retransmission and Fast Recovery. Based - With mobile robot being applied to military area、manufacturing and daily llife etc,it is an active and promising research area and attracts much more attention. Mobile robot’S localization and navigation based on stereo vision is becoming one of important research direction of intelligent robot.In this thesis,the problem of canlera calbiration、object feature extraction and feature matching,as well as object localization have been investigated in details based on AS—RF research platform,These algorithm are implemente - As the rapid development of artificial intelligence technology,computer technology, electronic technology and signal processing,robot technology has made tremendous progress in recent years and the applications of the robot technology is also very extensive.Various types of robots in the industrial,agricultural and military have been developed currently and these robots bring great convenience to the life and work. - This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based sampling techniques. The proposed control scheme preserves all well-known individual advantages of GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an important reduction of actuation load meanwhile the control system performance is maintained within an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish a tradeoff between control performance and the number of actuations. The performance of the proposed control algorithm is first verified for a first-order plus delay process and afterwards it is uated by using a case study based on the greenhouse temperature control problem. - An original proposal of using SRO-based receiver to demodulate QPSK signals is presented. The receiver is composed of an LNA and a super-regenerative oscillator (SRO), both combined in a single stacked config- uration for current reuse. The demodulation of received RF signal is performed via a novel digital circuit capable of detecting phase information embedded in the SRO output. The receiver is able to demod- ulate incoming signal without the need of an LO, PLL or an ADC. The complete receiver was designed using a 0.13 m technology and pre-layout simulation confirms proper and efficient operation, where the designed receiver operating in the 402–405 MHz MICS band shows 135 W power consumption, while being able to properly detect and extract sent informatio - Against the serious overload situation of the Vx traction transformer secondary Side FN winding serious problem of three-phase side of the negative sequence,the program of replacing Vx traction transformer is put forward,and direct power supply scheme of introducing the dual windings in parallel of W+晰m strengthen line is proposed,as well as the balance compensation scheme.A detailed analysis of the balance compensation program is carried out,and a based Smile Var Generator(SVG)traction transformer balanced - This paper presents the modeling and implementation of a three-phase DSTATCOM (Distribution Static Compensator) using STF (Self Tuning Filter) based IRPT (Instantaneous Reactive Power Theory) control algorithm for power quality improvement. It is used for harmonics elimination, load balancing and reactive power compensation at distorted PCC (Point of Common Coupling) voltages under nonlinear loads. An adaptive fuzzy logic controller is used to control the dc bus voltage of VSC (Voltage Source Converter) based DSTATCOM to improve the response and to reduce the overshoot and undershoot of traditional PI (Proportional-Integral) controller under unbalanced loading conditions and supply voltage fluctuations. - This paper presents the modeling and implementation of a three-phase DSTATCOM (Distribution Static Compensator) using STF (Self Tuning Filter) based IRPT (Instantaneous Reactive Power Theory) control algorithm for power quality improvement. It is used for harmonics elimination, load balancing and reactive power compensation at distorted PCC (Point of Common Coupling) voltages under nonlinear loads. An adaptive fuzzy logic controller is used to control the dc bus voltage of VSC (Voltage Source Converter) based DSTATCOM to improve the response and to reduce the overshoot and undershoot of traditiona - tMissing data in large insurance datasets affects the learning and classification accuracies in predictivemodelling. Insurance datasets will continue to increase in size as more variables are added to aid inmanaging client risk and will therefore be even more vulnerable to missing data. This paper proposes ahybrid multi-layered artificial immune system and genetic algorithm for partial imputation of missingdata in datasets with numerous variables. The multi-layered artificial immune system creates and storesantibodies that bind to and annihilate an antigen. The genetic algorithm optimises the learning processof a stimulated antibody. The uation of the imputation is performed using the RIPPER, k-nearestneighbour - This paper analyses the Proportional-Integral-Derivative (PID) controller’s performance for quadruple tank process. The selection of controlling the flow ratios in quadruple tank process act as Minimum and Non-minimum phase system. Its performance can be affected when system is shifted minimum to non-minimum phase configuration and vice versa. This paper mainly focuses on searching the optimal controller structure by increasing the controllers’ performance criteria. A comparative study on different controllers’ structures responses are in the presence of peak overshoot. A simulation study of PID controller and Modified PID controller structures have been designed and to analyzed the different controllers’ performance for the minimum and non-minimum phase system - In order to solve the power quantity problem of negative sequence current and harmonic current in high-speed railway, railway static power conditioner (RPC) was adopted. RPC contains two inverters which are connected with each other by sharing a DC capacitor, the negative sequence current and harmonic current can be restrained together by controlling the power of the two inverters. The structure and compensation principle of RPC was introduced, and the negative sequence current and harmonic current compensating reference detecting method for three-phase Vv transformer was presented. To maintain the DC voltage and compensate negative sequence and harmonic current, - We propose a new class of models for image restoration and decomposition by functional minimization. Following ideas of Y. Meyer in a total variation minimization framework of L. Rudin, S. Osher, and E. Fatemi, our model decomposes a given (degraded or textured) image u0 into a sum u+v. Here u ∈ BV is a function of bounded variation (a cartoon component), while the noisy (or textured) component v is modeled by tempered distributions belonging to - In this paper, we propose a method to accelerate the speed of subset query on uncompressed images. First, we change the method to store images the pixels of images are stored on the disk in the Hilbert order instead of row-wise order that is used in traditional methods. After studying the properties of the Hilbert curve, we give a new algorithm which greatly reduces the number of data segments in subset query range. Although, we have to retrieve more data than necessary, because the speed of sequential readings is much faster than the speed of random access readings, it takes about 10 less elapsed time - An inventory of all possible homogenous Hilbert curves in two dimensions are reported. Six new Hilbert curves are described by introducing the reversion operation in the construction algorithm. For each curve, the set of affine transformation defining the generation process is reported. Finally, each curve is also described in terms of a tag system. - As large enterprises, there are a lot of emotional load, power grids need to absorb the large number of non-functional capacity, the electricity sector in order to save power and improve the quality of power, the need for reactive power compensation system.Thyristor switched capacitor(TSC)is a new direction of the static vat compensator(SVC)technology . The characteristics of its various main circuits are analyzed . Some key problems on developing TSC device are introduced including the criterion of switched capacitor , the data detectionmethod , zero—voltage switching—on and the triggering circuit for thyristors - which are cascaded by bridge cells with delta configuration (SDBC) and cascaded by chopper cells with double star configuration (DSCC). The negative sequence current compensation mechanisms of SDBC converter and DSCC converter are different, it needs further study which kind of topology is more to identify. This paper expounded the negative sequence compensation principle of the SDBC-SVG and the DSCC-SVG, and deduced the circulation current and bridge arm currents mathematically. The correctness of the derivation was validated by PSIM simulation. Through contrastive analysis of bridge arm currents stress and the installed capacity of two kinds of modular multilevel SVGs, it was found that the negative sequence compensation characteristics of DSCC-SVG are superior to SDBC-SVG. The conclusion provides a theoretical reference for making reasonable selection of negative sequence compensation topology in engineering applications. - A hybrid Firefly Algorithm (FA) and Pattern Search (PS) optimized fuzzy PID controller is proposed for Load Frequency Control (LFC) of multi area power systems. Initially a two area thermal system with Governor Dead Band (GDB) nonlinearity is considered and the gains of the fuzzy PID controller are optimized employing a hybrid FA and PS (hFA–PS) optimization technique. The supremacy of proposed hFA–PS over FA is also demonstrated. The advantage of the proposed fuzzy PID controller has been shown by comparing the results with some recently published techniques, such as Differential Evolution (DE) and Craziness based Particle Swarm Optimization (CPSO). Further, sensitivity analysis is performed by varying the system parameters and operat - By analyzing the mathematical model of the three-phase pulse width modulation (PWM) current-source rectifier (CSR) in a stationary reference frame based on the instantaneous power theory, a voltage-oriented CSR power control strategy was proposed. As an alternative approach for active damping, the proportional capacitor-voltage feedback was used to damp the inductor-capacitor filter (LC) resonance. The system transfer function of the inner-current loop was analyzed using the frequency response method. In order to improve the limitations on dynamic response and stability of the controller,a new cascaded lag - of L. Rudin, S. Osher, and E. Fatemi, our model decomposes a given (degraded or textured) image u0 into a sum u+v. Here u ∈ BV is a function of bounded variation (a cartoon component), while the noisy (or textured) component v is modeled by tempered distributions belonging to the negative Hilbert-Sobolev space H − s . The proposed models can be seen as - target shocks for event study. Event study method is used to model the effects of oil price shocks on China’s gross domestic product, consumer price index, exchange rate, and gross imports and exports. Empirical results show that oil price shocks negatively affect China’s GDP and exchange rate but positively affect China’s CPI. It is also found that severer oil price shock may cause more significant impacts on China’s imports and exports field. Finally, such results are compared with those existing researches, which are most representative and compatible with our case. This paper is the first quantifies the oil price shock intensity, and verifies the hypothesis that macroeconomic impacts of oil price shocks - Cell centered (LAPc) and cell edge (LAPe) algorithms were developed to solve the static neutron diffusion equation in 2D Cartesian geometry using Lagrange interpolation with the progressive polynomial approximation. Two benchmark problems were used to test the algorithms the two-group TWIGL problem and a one-group IAEA benchmark problem. The LAP algorithms showed to be more accurate than a finite difference method (FDM) and for about the same level of accuracy, the LAP numerical methods have an efficiency advantage because they have to solve for less number of unknowns. The LAP algorithms showed more sensitivity to the mesh size than what QUANDRY results showed. Even though the FDMs algorithm, for the calculation of keff, showed systematically to be less accurate than QUANDRY, LAPc, and that LAPe, it was the only one that did not produce negative flux in any location for all the mesh structures analyzed in the IAEA problem. Other variants of - With development of the Internet and computer technology,the network has become all integral part of society.In the network,generation of network congestion will cause some big problems,such as increased network transmission delay, increased packet loss rate,or even a meltdown of the network.Therefore,network congestion control mechanism iS required in the network communication protocol on the mainpart. - Industrial CT (ICT), is composed of many subj ects, such as automatlon, commullic“on engineering,mechanical engineering,optoelectronlc technology and image processing,etc.ICT is also n锄ed Computer Tbmography technology(the best testing tecllll0109y at present),which印plies to i11dustrial products for non‘destmc‘1Ve testing. - This paper focuses on classes of remote monitoring and control applications where important functionality is required at low cost a new methodology for monitoring and control is proposed where the processing is based on firmware on an off the shelf microcontroller. Sensing can range across a number of physical parameters and communication is based on exploiting existing infrastructure in particular support for TCPIP. Flexibility, low cost, low maintenance are key drivers - The paper deals with representations of the safe states set in the Banker s problem. Using a Petri Net model we derive formulas for this set (SAFE) directly and for its (smaller) minimal elements set MIN. Moreover, we partition the set MIN into subclasses, so that two elements of the same subclass only differ by the permutation of their components. The set SORT, which contains only one representend of each subclass, is an even smaller representation of the safe states. We also derive estimates for the size of SORT. Finally we investigate, how our results can be translated to the multidimensional Banker s Problem, where credits in more than one currency can be given - There are three methods for handling deadlocks in resource allocation systems deadlock prevention, deadlock avoidance and deadlock detection combined with recovery. Of these three methods deadlock avoidance is preferable in many cases but seldom used on account of its high cost. We present a simple modification of a known deadlock avoidance algorithm, the banker s algorithm, which has a running time O(mn 2) in a system consisting of n processes and m different types of resources. Our modified algorithm gives an amortized worst case running time of O(mn) under certain likely conditions and in that way it can be considered a competitive method for handling deadlocks. At worst, our algorithm is twice as fast as the banker s algorithm, - Our contribution here is to design efficient distributed algorithms for the maximum flow problem. The idea behind our distributed version of highest-label preflow-push algorithm is to disseminate label values together with safety information every node. When the algorithm terminates, the computed flow is stored distributedly in incident nodes for all edges, that is, each node knows the values of flow which belong to its adjacent edges. We compute maximum flow in O(n 2 log 3 n) time with communication complexity O(n2(log 3 n + V~)), where n and m are the number of nodes and edges respectively in a network graph. - In order to effectively manage the problem of load frequency control (LFC), preserve stability of frequency, tie-line power and area control error (ACE) for inter-connection hydro power system, the optimal problem between system parameters and controller parameters was constructed in this paper according to the relation between the maximum peak resonance and the maximum peak overshoot. The mathematic expression between the two kinds of parameter was obtained by deduced the optimal problem. Aimed at the non-minimum phase character of hydro generator - This paper presents an Artificial Immune System approach for solving generation scheduling problem of a Genco comprised of thermal and wind energy systems. Wind–thermal scheduling problem determine the time of instant to start up and shut down the generating units over a scheduled time period, while satisfying the ‘system’ and ‘generator’ constraints including minimum up/down time ramp rate limits of thermal units and wind power constraints. In this work, the impact of wind energy on short term generation scheduling problem is analyzed through the adaptive search which is inspired the Artificial Immune System. The effectiveness of the proposed approach is demonstrated through a Genco consis - This article presents a simulation model of Space vector Pulse Width Modulation (SVPWM) Rectifier using MATLAB/Simulink which ability is to stabilize an output voltage of 500 Vdc a 3 phase 300V system using a decoupling feed-forward control method by dq frame technique. The model is tested due to a variation of ± 10 of rated input voltage. From the simulation model, it can use for implementation into a real-time control system by Digital Signal Processing Board (such as DS1104). Together, it also can be designed into a real circuit easily and effectively. The experimental results show that the SVPWM Rectifier which is presented in this paper has an adequate performance which can be applied widely - Predictive direct power control (P-DPC) applied to voltage source pulse-width-modulation (PWM) rectifier was introduced in this paper. Based on the model of power prediction, voltage vectors were selected according to minimizing power errors in a fixed time interval, which results in a constant switching frequency control for P-DPC. It simplifies the implementation of P-DPC procedure by selecting switching states based on the principle of space vector modulation (SVM). In order to eliminate power errors caused by control delay, a detailed control delay compensation scheme was designed. Experimental results based on a 2kW prototype were presented, which showing that P-DPC has a faster power response compared to standard voltage-oriented-control (VOC) techniques. Besides, the dynamic performance of the system is also improved significantly by control delay compensation. - tA scheme of format conversion optical 16-ary quadrature amplitude modulation (16QAM) toquadrature phase shift keying (QPSK) signal based on cascaded four-wave mixing (FWM) in semiconduc-tor optical amplifiers (SOAs) is proposed. Theoretical analysis and simulations of the format conversionscheme are conducted to validate the feasibility of the proposal. In this proposal, the phase conjugatedof 16QAM signal is generated after the first FWM process in an SOA, and then the QPSK signal is con-verted due to the second non-degenerate FWM (ND-FWM) process in another SOA. The performance andthe optimal design of the 10 Gbit/s format conversion system under various key parameters of SOAs are uated and discussed. Simulation results present useful to enable interconnection between backbonenetwork and access network. - An all-optical regeneration scheme for DQPSK and QPSK signals using phase-sensitive amplifiers (PSAs) is studied and its effectiveness is investigated through numerical simulations. By leveraging the ability of PSAs to provide phase and amplitude regenerative amplification, we show significant simultaneous suppression of both phase and amplitude noises of (D)QPSK signals under optimized conditions. The reduction in the phase noise variance of a noise-corrupted DQPSK signal obtained by one such regenerative amplification can be as large as 5.5 folds, showing its good potential for distributed optical regeneration of (D)QPSK signals.  2008 Elsevier B.V. All rights reserved. - High temperature will affect the stability and performance of multi-core processors. A temperatureaware scheduling algorithm for soft real-time multi-core systems is proposed in this paper, namely LTCEDF (Low Thermal Contribution Early Deadline First). According to the core temperature and thread thermal contribution, LTCEDF performs thread migration and exchange to avoid thermal saturation and to keep temperature equilibrium among all the cores. The core temperature calculation method and the thread thermal contribution prediction method are presented. LTCEDF is simulated on ATMI simulator platform. Simulation results show that LTCEDF can not only minimize the thermal penalty, but also meet real-time guarantee. Moreover, it can create a more uniform power density map than other thermalaware algorithms, and significantly reduce thread migration frequency - In the distributed processing, where common labeled data may be not available for designing classifier ensemble, however, an ensemble solution is necessary, traditional fixed decision aggregation could not account for class prior mismatch or classifier dependencies in electronic technology. Previous transductive learning strategies have several drawbacks, e.g., feasibility of the constraints was not guaranteed and heuristic learning was applied. We overcome these problems by developing improved iterative scaling (IIS) algorithm for optimal solution. This method is shown to achieve improved decision accuracy over the earlier approaches in electronic technology - This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting multiple minimizers are described. Moreover, results on the ability of the PSO in tackling Multiobjective, Minimax, Integer Programming and 1 errors-in-variables problems, as well as problems in noisy and continuously changing environments, are reported. Finally, a Composite PSO, in which the heuristic parameters of PSO are controlled by a Differential Evolution algorithm during the optimization, is described, and results for many well-known and widely used test functions are given. - Direct sequence spread spectrum (DSSS) communication systems has been widely used in these years for its advantage of wide spectrum, low working Signal-to-Noise ratio (SNR), anti-interference, anti-multipath effect and capability of LPI and LPD. They are increasingly replacing conventional communication forms and obtaining extensively applications in modern military and commercial communication systems, for example, CDMA communication system, GPS , measuring and control system, satellite chain, identification of friend or foe and etc. Therefore, corresponding DSSS electronic counter technique becomes a big problem to solve in electronic warfare domain. DSSS electronic counter technique including blind detection, blind parameter estimation and spreading sequences estimation. For the issue of DSSS electronic counter technique of DSSS/QPSK signal damaged by strong additive white Gaussian noise (AWGN), the main research content in this dissertation as follow. - Considering the complete process of surgery including the preoperative and postoperative stages, multiple resource constraints involved and the integration of surgical upstream and downstream resources, surgery scheduling was described as an extended multi-resource constrained flexible job-shop scheduling problem and an optimization approach was proposed based on an improved ant colony algorithm. A resource selection rule and strategy of overtime judging and adjusting was designed, and the scheduling process with the ant colony algorithm was realized. The case study shows that the improved ant colony algorithm proposed in this paper achieved good results in shortening total time and allocating resources for surgery scheduling - 无边活动轮廓模型(C-V模型)是水平集分割方法中的一种经典模型.传统的无边活动轮廓模型将灰度同质作为区域分割准则,这使其对于仅含两个同质区域且灰度变化不大的图像能够取得很好的分割效果,但对灰度渐变图像分割时,该模型往往无法得到正确结果.本文针对这一问题,通过引入Chebyshev距离构造一种新的相似度,以此来表征演化曲线内外灰度差异,修改了传统无边活动轮廓模型中均值取值的定义,使得演化曲线在图像灰度变化缓慢区域获得较大的驱动力.新模型克服了传统无边活动轮廓模型不能正确分割灰度渐变图像的不足.实验对比及分析表明,新模型能够更准确地分割灰度渐变图像,同时对噪声有一定的鲁棒性. - QPSK 调制全称 Quadrature Phase Shift Keying,意为正交相移键控,是 一种数字调制方式。它的频带利用率高,且抗干扰性能强,已经成为现代通信 技术中一种十分重要的调制解调方 - Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation - This work describes a framework for image hiding that exploits spatial domain color properties of natural images combined with spectral properties of the Fourier magnitude and phase of these images - A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach - Image steganography technique is widely used to realize the secrecy transmission. Although its strategies on classical computers have been extensively researched, there are few studies on such strategies on quantum computers. Therefore, in this paper, a novel, secure and keyless steganography approach for images on quantum computers is proposed based on Moir´ e pattern. Algorithms based on the Moir´ e pattern are proposed for binary image embedding and extraction. Based on the novel enhanced quantum representation of digital images (NEQR), recursive and progressively layered quantum circuits for embedding and extraction operations are designed. In the end, experiments are done to verify the validity and robustness of proposed methods, which confirms that the approach in this paper is effective in quantum image steganography strategy. - Color can provide an efficient visual feature for tracking nonrigid objects in real-time. However, the color of an object can vary over time dependent on the illumination, the visual angle and the camera parameters. To handle these appearance changes a color-based target model must be adapted during temporally stable image observations. This paper presents the integration of color distributions into particle filtering and shows how these distributions can be adapted over time. A particle filter tracks several hypotheses simultaneously and weights them according to their similarity to the target model. As similarity measure between two color distributions the popular Bhattacharyya coefficient is applied. In order to update the target model to slowly varying image conditions, frames where the object is occluded or too noisy must be discarded. - uC/OS内核任务调度模块的分析与改进,对做嵌入式开发的很大帮助 - 纹理图像分割论文+代码,对图像处理的有帮助 - 图像分割源程序,GAC模型,对做图像处理的有帮助

Download log:
morphology.rar - 形态学实现代码,腐蚀,膨胀,开运算,闭运算等 - 鼠标点击按钮,启动线程,马上开始计数, 在Edit中显示,一秒钟刷新一次。
CreateThreadExample.rar - 一个基于对话框的多线程程序的例子,主要示范了如何应用CreateThread
CreateThread.rar - vc——使用Win32 API创建、销毁线程——控制进度条\CreateThread
DENTIST-master.rar - 红外小目标检测算法RIPI,基于红外块图像,张量加权,PCA
CT_code_v0_hist.rar - 改进的压缩感知的红外小目标跟踪。将原始特征由haar特征替为直方图。初始时用tophat增强小目标。 - 简单的多线程例,简单的多线程例子.子,简单的多线程例子 - C++ 多线程,和多线程锁,多线程同步的简单实例, 思路清晰简单, 可以借鉴。 - C++ 多线程测试代码,使用多线程处理.C++ 多线程测试代码,使用多线程处理.
duoxiancheng.rar - 多线程...............多线程
New_PTZ_CONTROL.rar - 新 Pelco D 的控制命令,在原有的基础上把整个程序补全,可以正确编译
ptz_control.rar - 用c++编写的云台控制程序,可以实现云台的基本动作. - 图像平滑,L0范数,稀疏,锐化,滤波 通过限制非零梯度的数量来实现最高对比度边缘,同时以全局方式实现平滑 - 暗通道优先的单幅图片去雾算法,去雾效果明显,稳定性好
darkchannel.rar - 本代码实现了用暗通道去雾算法实现图像的去雾处理。 - EKF_UKF_PF三种算法的比较,仿真结果很明显。
KF_EKF__UKF.rar - 该程序用于比较KF、EKF、UKF滤波器的不同
EKF.rar - 本人写的关于EKF的小程序,适用于初学者
Infrared_Target_Detection.rar - 红外图像运动目标检测、识别与跟踪算法演示程序。附件:点目标到面目标完整图像序列
MFC+OpenCV图像处理.rar - MFC+Opencv,实现了opencv中的各种滤波、边缘检测、拉普拉斯变换及高斯变换等,源码。