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When we think of paper-folding, we usually think first of the name that is usually associated with it: origami. But in the field of architecture, origami is more than just imagining an animal or flower which is what this word usually brings to mind. In architecture, we extend the meaning to take in the real essence of the word – that of great structural and constructional loads. The basic unit of origami – the fold – allows us to start manipulating space and even to create space itself. Paper-folding, with its spatial modelling potential, is to three-dimensionality what drawing is to two-dimensionality. It is after all an ancient Japanese art which encapsulates the advantages of intuitive thinking and fast modelling, once the basic elements of folding are known. Heino Engel (2001) in his book “Structural Systems”, describes intensive studies on types of structures which derive from this systematization. And the architect Ming Tang often uses structures in his projects which clearly originate in the concept of origami, and he correlates these structures with sustainable materials. The architect Michael Hansmeyer manages to incorporate all the beauty of the action of folding with the help of a computer, where the final result is a shape that approaches a real application at an architectural level. Over time, there have been numerous people who have found a relationship between the harmony and proportions of paper-folding and their own studies and projects. What is missing is a single point where clear concepts on the possibilities of folding and the results of those who have experimented with it can be brought together. This cataloguing, which is being carried out in this Master’s dissertation, is intended to be a contribution to the design method in architecture, through which the architect may achieve spatial dexterity over a piece of paper.

College English examination is an important part of university English education, for the difficult problems in the process of examination organization and management, in this paper, the intelligent test paper composition research based on genetic algorithm. First, basic research, including the basic idea of genetic algorithm, algorithm flow and perform operations on groups; then, studies test paper composition model, the test paper problem described as question number, question types, difficulty, discrimination, score, answer time, using the frequency property and other attributes, constituted seven dimensional vector. Finally, test paper composition design, to generate the initial population, fitness function design, operation operator design, algorithm terminates and others, four key steps were designed. The content of this paper to meet the quality and speed requirements of university English test paper composition, and has the advantages of randomness, scientificalness and so on.

As a important part of teaching, Traditional paper analysis algorithm is complicated and not comprehensive enough. This paper according to the indicators of education measurement and improves the traditional calculation models, the system assesses the perfect calculation model, The teacher also can get the true and fast reaction to students' knowledge and the quality of the paper. This method thereby provides a convincing basis for the improvement on the future teaching and increase the effectiveness in teaching

The color reproduction is based on visual perception. The psychophysics experiments present the light source; illuminants and view background affect the results of color matching. Paper is a typical substrate for printed color matching and effects printed color greatly. Now almost all of print papers contain optical brightening agents, which changes significantly the color appearance of printed color and makes color shifting of printed color matching. This paper used CAT02 chromatic adaptation models to transform the measurements of printed color in paper with and without OBA, compared the effect of printed color matching between before and after transforming with display, present the method using chromatic adaptation transforms to improve the accurate of printed color matching.

The prediction of color appearance is the basic theory and technology in modern color science field. The aim of this study is to evaluate the color appearance of packaging and printing atlas. This paper took high gloss double-sided coated paper color printing atlas as the experimental samples. The color samples are measured using ACS color-matching instrument under different light sources (D65, A and TL84), then based on color science and visual psychophysics methods, establishing the datasets of the samples’ color appearance. We use mathematical statistics methods, correlation coefficient R2 and coefficient of variation CV, to evaluate the visual prediction results in the color atlas, under three different light sources.

With the development of the concept of Industry 4.0, research relating to robots is being paid more and more attention, among which the humanoid robot is a very important research topic. The humanoid robot is a robot with a bipedal mechanism. Due to the physical mechanism, humanoid robots can maneuver more easily in complex terrains, such as going up and down the stairs. However, humanoid robots often fall from imbalance. Whether or not the robot can stand up on its own after a fall is a key research issue. However, the often used method of hand tuning to allow robots to stand on its own is very inefficient. In order to solve the above problems, this paper proposes an automatic learning system based on Particle Swarm Optimization (PSO). This system allows the robot to learn how to achieve the motion of rebalancing after a fall. To allow the robot to have the capability of object recognition, this paper also applies the Convolutional Neural Network (CNN) to let the robot perform image recognition and successfully distinguish between 10 types of objects. The effectiveness and feasibility of the motion learning algorithm and the CNN based image classification for vision system proposed in this paper has been confirmed in the experimental results.

Much progress has been made in the field of digital imaging technology with the widespread use of CMOS and CCD devices and the high computing power of IC chips. However, there still are many technological problems to overcome to achieve lightweight and affordable high density 3D lossless imaging for both industrial and scientific applications. This paper will focus on the latest development of freeform optical technology and powerful image analysis techniques to develop a compound eye camera system so as to extract the 3D relative position coordinates of the sub-object in the field of view, and to compensate the shadow effect in the images caused by the non-uniform illumination to obtain high quality lossless images. Such a novel compound eye system will find applications in delivering 3D image of digital camera, increasing capability of scientific profiling measuring instrument, and lowering cost and enhancing resolution of wide-field, video-rate, gigapixel cameras such as the AWARE designed by Duke University.The main objective of this paper is to design a novel compound eye system from high definition 3D lossless digital imaging technology to achieve the realistic three-dimensional positional information of the object in both near and far fields. In the imaging process, the ultimate imaging quality is affected and limited by the resolution of the detector, the field of view, wavefront aberration, resolution of the optical imaging system and the ambient light.The novel compound eye imaging system includes two modules: one is the optical imaging module with compound eye optical elements with other secondary optical lenses, while the other one is the image analysis module. By combining the above optical hardware with the image analysis software, the relative position information of the sub-objects in the picture and the lighting condition of the environment can be deduced accurately.

Robotics and automation are playing very imperative role in the modern construction practice to meet the challenges and expectation specifically in the infrastructural projects. Automation is a tool for operating or controlling different stages of construction process using mechanized and electronic devices or control systems to reduce the human intervention to a minimum. The design and implementation of these automation technologies has shown progressive outcomes compared to conventional methods. Moreover, considerable improvement in working condition, reduction in accidents and significant increase in production have been evidently observed in the recent construction projects as well as in the earlier research studies. Although several countries have adopted automation in their construction projects, application of these techniques in India is limited to a greater extent due to lack of proper guidelines and specifications. It is important to develop appropriate standards and guidelines for Indian construction sector. This paper reviews different automation techniques that are currently used in many parts of the world and suggestions for their application in the Indian construction scenario are discussed in detail. Moreover, guidelines for efficient design and implementation of automation techniques in India are highlighted in this paper.

In this paper authors conducted analysis of management features on machine-tools with numerical control using neural network for achieving exactness. Applications of Hopfield networks are discussed in the paper along with application of neuron computers that offer decision making of tasks ticker-coil.

The paper describes an experimental determination of kinematic quantities using high-speed digital image correlation system. It deals with the analysis of minimal sampling frequency needed for correctly performed high-speed correlation analysis. The authors also describe the influence of cameras sampling frequency on the quality of the obtained results. Mentioned analysis was performed using a rotational object. For the purposes of the results comparison the data obtained from correlation system in a form of displacements in three mutually perpendicular directions were processed in Matlab and in the paper are depicted in a form of graphical visualizations.

The aim of this paper is to presents an interdisciplinary approach to the problem of manufacturing process support using Artificial Intelligence (AI) by introducing a cross physical-information control system concept. The scope of the article covers description of logical architecture concept, data exchange process and autonomous steering mechanism using artificial intelligent method. The article indicates that in order to successfully support manufacturing process using Artificial Intelligence proper logical support system architecture need to be applied. It is important to emphasize that the use of AI method is not enough to cover multidimensional production issues of gathering and processing data. Therefore whole system need to be organized in this way to support AI with data to be processed. Thanks to that, it is possible to meet many different goals and achieve significant results in the field of manufacturing process. Because of that in this paper the main focus is put on system logical architecture with descriptions of each element involved. Moreover, the article describes AI controller mechanism applied running on real time raw data collected from machines and products. Findings presented within paper could be use in real case scenarios as a design pattern to develop, deploy or optimize production management systems in small-medium enterprises based on low cost solutions of Internet of Things (IoT) providing data to be analyzed with use of cloud computing technology running AI algorithms.

This paper presents an overview of the state of art of mobile robots presenting aspects of their current level of sophistication, fields mobile robots are being presently used, the future application and scope of mobile robots. Classifying the primary research topics of multi-robot systems into seven major categories (Biological inspirations, architecture, localization/mapping/exploration, object transport and manipulation, motion co-ordination, reconfigurable and learning robot systems, vision), we discuss the current state of research in these areas. An attempt to cover the points for which a general agreement has emerged within the scientific domain, are then presented, followed by a discussion of alternative approaches and currently unsolved problems. This paper also reviews the most relevant literature and previous research activity regarding mobile robotics. We conclude by identifying more topics of scientific consensus, open research issues and a discussion of some application areas where mobile robots could be used with existing technology.

This paper proposed a spelling error detection and correction using the linguistic features and knowledge resource. The linguistic features mainly come from language model that describes the probability of a sentence. In practice, the formal document with typos is defective and fall short of the specifications, since typos and error hidden in printed document are frequent, rework will cause the waste of paper and ink. This paper proposed an approach that addresses the spelling errors and before printing. In this method, the linguistic features are used in this research to compare and increase a new feature additionally that is a function of Internet search based on knowledge bases. Combining these research manners, this paper expect to achieve the goals of confirming, improving the detection rate of typos, and reducing the waste of resources. Experimental results shows, the proposed method is practicable and efficient for users to detect the typos in the printed documents.

In this paper, several data mining techniques were discussed and analyzed in order to achieve the objective of human daily activities recognition based on a continuous sensing data set. The data mining techniques of decision tree, Naïve Bayes and Neural Network were successfully applied to the data set. The paper also proposed an idea of combining the Neural Network with the Decision Tree, the result shows that it works much better than the typical Neural Network and the typical Decision Tree model.

It is important to obtain the 3d coordinate in the field of measuring. How accurate, fast, convenient to obtain the 3d coordinate affects the accuracy and reliability of measurement directly. Through studying the basic theories of machine vision this paper focus on the study of a stereo vision measurement model based on the intersecting axis. In view of the parameters in the model of binocular stereo vision, this paper uses the Zhang Zhengyou calibration method to calibrate the system of Stereo vision. In order to test the accuracy of the system, this paper measures the distance of two standard circular. Finally, the machining experiment validates the proposed method.

At present P2P is widely applied on the Internet. But it still has a safety hazard because of the special feature of dynamic and anonymity of P2P.This paper designs a model of P2P trust based on fuzzy degree of nodes' credit. It computes the fuzzy degree of nodes' credit according to the historic records and the theory of fuzzy mathematics, and the result is used as the basis of choice of P2P transaction. The fuzzy degree of nodes' credit will be increased and decreased according to the behavior of the node, establishing the dynamic and reasonable mechanism of rewards and punishment. Experimental results show that the model designed in this paper has a better performance in the parts of trade success rate and network load.

Golf has become an increasingly popular sport. Determination of motion parameters of golfball can give quantitative suggestion for players. This paper introduces the principles of determinationbased on Doppler radar. The parameters of golf motion to be measured include velocity, angle, spinangular velocity and position. A golf realtime tracking system is designed with one transmitting antennaand three receiving antennas in this paper. Simulations validate the feasibility and high accuracyof this system. This system makes referential significance for golf realtime tracking system.

This paper analysis the characteristics of High Spatial Resolution Remote Sensing Image (HSRRSI), consider the drawback of pixel-wise Classification, an Object-based method was taken to classify the image. The paper firstly preprocess and coarsely segment the image, secondly optimize the segmented results for deeply processing, then extracting the image feature from the original image and segmented results, finally classify the image and assess the results.

In tracking object by a camera, the jolting of the vehicle will increase the deviation of the skewing value of the air object in the image. a method of image stability based on digital inclinometer is presented in this paper. The incline angles caused by the jolting of the vehicle are measured by the angle sensor, and the incline angles are used to eliminate the object image deviation caused by jolting and to stabilize the object image. The method for acquiring the height of object by a single camera is also discussed in the paper during the process of extracting the image deviation. The extraction errors of the deviation are analyzed and simulated; the simulation results show the efficiency of the method.

A Chinese web-page classification algorithm based on SVM including the important aspects of text preprocessing, feature selection and multiple-Classification algorithm. In this paper, based on the analyses of features of Web documents, this paper does research the approach of classification in Support Vector Machine (SVM) and select of Kernel function. Furthermore, a web-page classification model and algorithm that is based on Binary Tree SVM is presented. The experiments show that it not only reduces the size of train set, but also has very high training efficiency. Its precision and recall are better.

The paper analysis mean filter, median filter and morphology filter. The paper studied order morphology theory and its filter character. Based on this, the paper proposed multi-scale and multi-structure filter algorithm based on order morphology. The result of simulation shows that the algorithm can not only keep the edge and detail of medical image but also can enhance the contrast of recovery image.

Stereo matching methods are widely used in computer vision and stereo reconstruction, from the perspective of improving the matching accuracy, this paper focuses on the global optimization algorithm. An improved Belief Propagation method is proposed in this paper, by involving more pixels into information transmission, our method improves the accuracy ofstereo matching. The experimental results verify the efficiencyand reliability of our method.

The query of database must rely on professional query language, which is difficult to grasp for ordinary users. Natural language query interface (NLQI) can be applied to solve this problem with better human-computer interaction and intelligence. However, current natural language understanding technology is not mature. Though the query sentences’ structure is fixed, it is also difficult to accurately convert query sentences into understandable database query language for computer. Therefore a method of designing NLQI based on syntax and semantic analysis is proposed in this paper. First of all, Maximum forward and maximum reverse matching algorithms are used to analyse sentence by part of speech (POS) template, which is able to demonstrate the syntax relationship among the words. After syntax analysis, query conditions and targets are identified. Then, single conditions and targets are analyzed to relative standard forms by the relationship among entity, property, connect verb and unit. At last, these standard forms are transformed to SQL sentence. Regarding printing ERP system as experimental subject, experiment is done in this paper. The result shows that the method proposed in this paper can meet the needs of natural language query, and has a good transform effect for combination, omitting and other complex sentences.

In this paper ,a color printing defect automatic online detection method based on digital image processing technique is proposed. The main idea of this method is comparison of defect product and template and it makes up of following key models. Firstly, multi-scale segmentation is applied to composed image which is overlaid by detecting product and template image. Secondly, an automatic region similarity analysis calculation is taken to segmentation obtained in multi-scale segmentation. The color difference between detecting product and template can be calculated accurately. Thirdly, defect detection results can be obtained according to threshold segmentation. Finally, the characteristics and advantages are approved by experimental analysis and discussion. Algorithm parameters are adjusted and modified to improve the stability and effectiveness. Experimental results approve that color printing defect automatic detection method in this paper has the characteristics of effectiveness and applicability. And experimental results indicate that this method has the advantage of judging the defect types automatically.

Synthetic Aperture Radar (SAR) has become one of the important means for the ocean remote sensing detection of oil spills. The existing SAR image segmentation method has the issues of edge blur, poor contrast, non-uniform intensity image, so the segmentation effect is not ideal. This paper presents a variational level set SAR image of oil spill detection method based on fuzzy clustering. First of all, apply the threshold method on initial segmentation of the original SAR image to transform the initial segmented image as fuzzy clustering. Secondly, introduce the clustering results into the initial level set function to achieve the initial contour. Finally, add fuzzy clustering model in the level set energy function to complete the level set evolution process and get the final segmented image. This paper uses the threshold segmentation results to achieve the initialization of the variational level set function profile. In theory, it could improve the level set method for efficiency, and reduce the wrong segmentation phenomenon. The experimental results show that the SAR image segmentation method of oil spill has good segmentation qualities and is suitable for the edge complex image segmentation.

Gesture has different speed in the process of movement. To reflect the different speed of the user, this paper presents a gesture speed estimation method. Firstly, we use data glove and camera to establish the relation between the variation of gesture contour and that of gesture speed. Secondly, we build the gesture speed estimation model by stages. Finally, we get the real-time speed of hand motion through this model and complete interactive task. The main innovation of this paper is that we reveal the relation between the gesture contour and speed to lay the foundation for further capture the interaction of user intention. Experimental results indicate that the time cost of our method decreased by 31% compared with freehand tracking based on behavioral models and the 3D interactive system based on our model is of high the user experience.

Traffic flow video processing is an important direction of the development of intelligent transportation, Gaussian mixture background modeling is one of commonly algorithms to build background modeling that is widely used in image processing field. In order to analysis the algorithm comprehensively ,in this paper, it calculus on formula as well as tests and compares some traffic flow videos, the solution based on the K-means, EM parameters model are presented, it gets the mathematical meaning and evolution process of the algorithm clearly by calculating formulas to provide theoretical guidance for practical application; the traffic flow videos processing can get the treatment ability of this algorithm according to the different situation of videos, analyze the mixed Gauss background modeling for time migration, the light changing, moving object shadow processing ability. In this paper, the algorithm of mixed Gauss background modeling is analyzed from two aspects of theory and application.

The paper put forward a new aided translation's pattern, Bilingual Assisted Translation Search Engine. It's different from traditional machine translation, does not rely on the computer's automatic translation, but according to relevant translation list given by system, and get the correct translation by people. Compared with automatic translation machine, it has better quality; compared with artificial translation, it has more efficient. For users, the relevant translation we provide more accurate and matching unless there is a large corpus, so the core of the system is the construction of the bilingual corpus. The paper adopted the method of web data mining and search engine technology, completed the construction of large-scale corpus automatically.

Mechanical drawing language EQS, its full name is Equally Spaced, which means the uniform distribution of meaning. Now, its importance is more and more incarcerating. This paper outlined the application of EQS in Applied Linguistics, firstly introduces the general situation, then describes the modeling steps; finally applied linguistics tells the story of EQS. In this paper, it mainly used the literature review method and literature survey.

With the improvement of computer hardware and software performance, digital multimedia technology has been applied to various fields. The visual effect of ceramic art image is affected mainly by the brightness, texture and color, in which the image defects will affect the visual effect of the ceramic product. This paper designs the digital processing system of a new ceramic art image processing, the system can repair defects in ceramic art image. In order to verify the validity and reliability of digital processing system, the lead-free perovskite structure BZT based ceramics is prepared in this paper, and the use of electron microscope and digital camera take the ceramic products processing image with artistic defects, and then using VB programming digital image processing technology carries out color re coating for the ceramic, the ceramic products electron microscopy images after restoration will be obtained by the image boundary restructuring, which provides a new computer method for the processing art of the ceramic products.

With the development of computer graphics, real-time rendering-based VF: technology has been applied in more and more fields. LOD is the key technology in large-scale terrain rendering. In this paper, the basic concept of LOD is introduced briefly and some algorithms of LOD in use are mentioned and analyzed; secondly as one of algorithms of LOD, View-Dependent Progressive Mesh algorithm is studied and improved, the result of implementing the large-scale terrain’s LOD by using VDPM is presented. There are key technologies in LOD Large-scale terrain real-time rendering are researched. Relative technologies are presented such as: LOD of the terrain, visibility culling, and cracks eliminate, view-dependent refine, LOD error, technologies of texture etc. Using LOD technology, VR system can greatly reduce the; number of polygons produced in real-time rendering procedure. Finally, we do experimental design work based on the methods and techniques presented by this paper.

this paper uses a new genetic algorithm (New Genetic Algorithm, NGA) to implement the automatic group volume function, solving the problem that the paper is not fully considered scores distribution of knowledge points in the test paper (test dimension) in the system using traditional genetic algorithm (Genetic Algorithm, GA) to implement automatic group volume, putting forward and redefining the fitness function to speed up the convergence. Simulation experiments show that the NGA algorithm is not only efficient, but can generate a valid paper, making the paper score can on the multi-dimensional of the test as far as possible to achieve uniform distribution.

The paper introduces the recent advances of machine translation technologies by decrypting several famous machine translation systems, and discusses the trend of the future development. The application of machine translation is introduced at last. In this paper, machine translation of the core of a few, summed up the machine translation system framework, discussed the modeling machine translation factors should be taken into account, a detailed analysis of segmentation, alignment sentence, the translation of knowledge acquisition, translation clips choice and in the machine translation: Generation's role in the process, completed a Machine Translation modeling, achieving a machine translation system.

This paper presents a novel approach to detect unattended and removed objects from a single fixed camera video for surveillance applications. In this paper two backgrounds rather than any tracking information are employed to detect static foregrounds. Each of the backgrounds is modeled by three Gaussian mixtures. We make a subtraction between two foregrounds extracted by the background subtraction method to initially determine the static regions. Then the region-level density analysis and texture information are combined to remove false static foreground regions caused by illumination changes and objects that are in the static-moving transitions. Finally, classification of the unattended and removed is determined by a method that compares color histograms of the static foreground zone and its extended areas in current frame. Experimental results show that our method can work well in simple scenario as well as complex environments with an unsmooth background.

Image fusion algorithm is very important in image fusion process. Image fusion algorithm based on pyramid decomposition was reviewed in this paper. Pyramid decomposition algorithm mainly includes Contrast pyramid, Gradient Pyramid, Laplacian Pyramid and Ratio Pyramid. The fusion algorithms based on pyramid decomposition were respectively applied in multi-focus images, advantage and disadvantage were summarized and application was given. Fusion results were given by MATLAB simulation. Objective evaluation index including of mean, standard deviation, entropy and average gradient was calculated in this paper. Image fusion algorithm should be selected according to the information extracted and the aim of fusion.

The paper researches a recognition algorithm of modulation signal and modulation modes. The modulation modes to be recognized include 2ASK, 2FSK, 2PSK, 4ASK, 4FSK and 4PSK modulation. There are two methods recognizing modulation modes of digital signal, method based on decision theory and pattern-recognition method based on feature extraction. The method based on decision theory is not suitable for recognition with multiple modulation modes. The core of pattern recognition based on feature extraction is selection of feature parameters. So the paper uses the feature parameters with simple calculation, easy to be implemented and high recognition rate as the core. The extraction of feature parameters is based on instant feature of modulation signal after Hilbert transformation.

This paper aims at the difficulty that lack of observation model and high-dimensional sampling in video tooning, proposes a method based on key frame matching and dual-directional Markov chain Monte Carlo sampling of video motion redirection. At first, after extracting the key frame of a given video, By affine transformation and linear superposition, the subject initializes the video’s space-time parameters and forms the observation model; Secondly, in each space-time, based on the bi-directional Markov property of each frame, This paper proposed a dual-directional Markov chain Monte Carlo sampling particle filter structure and takes full advantage of the relationship of the front and back frame of the parameters to estimate motion redirection parameters. At the same time, for high-dimensional sampling problem, the subject according to the directional parameters’ correlation implements classification of skeleton parameters-morphological parameters-physical parameters, proposes a hierarchical genetic strategy to optimize the output parameters and improves the efficiency of the algorithm. The research of this paper will produce an efficient and prominent animation expressive video motion redirection method and play an important role on video animation of the development.

With more and more researches about improving BP algorithm, there are more improvement methods. The paper researches two improvement algorithms based on quasi-Newton method, DFP algorithm and L-BFGS algorithm. After fully analyzing the features of quasi-Newton methods, the paper improves BP neural network algorithm. And the adjustment is made for the problems in the improvement process. The paper makes empirical analysis and proves the effectiveness of BP neural network algorithm based on quasi-Newton method. The improved algorithms are compared with the traditional BP algorithm, which indicates that the improved BP algorithm is better.

This paper mainly studies modeling and recognition of 3D English words’ images. With the development of secondary modeling, segmentation and recognition theories and the application of evolution computation in 3D modeling and recognition, this paper analyzes the issues of parameter fitting in the 3D model, multi-object scene segmentation and parts recognition aiming at the 3D data features in the English words. The 3D model is used as the primitives part to model and segment the scenes and the group parallel evolution and the relationship matching theories are introduced into the 3D modeling and recognition to deeply identify the rare English words’ images. The paper searches for a practical and efficient three-dimensional modeling and identification scheme.

This paper presents fuzzy color histogram feature-based image retrieval method and texture spectrum fuzzy histogram feature analyzes the image database indexing techniques and the introduction of the experimental system for an improved method of fuzzy indexes. Algorithm reflects the underlying characteristics of high-level concepts and integration, relevance feedback and machine learning mechanism combining ideas. In this paper, the algorithm full processing power of computer systems, has a certain reference value and practical significance.

In this paper, we propose an automatic preposition correction method for Chinese learners of English. Our corpus comes from Chinese learners of English Corpus (CLEC). We use N-gram model to extract the semantic features based on the form of the word in context, part of speech tagging and syntactic parse tree. Meanwhile, this paper proposes a new method based on mutual information and improves the training and classification method. This method’s performance has been improved in terms of both effectiveness and efficiency, and the results show a significant improvement compared with the previous results.

This paper presents a 3D gesture recognition technology based on machine vision as the center. Based on a large number of experiments, this paper sums up and introduces the existing gesture recognition technology, the key research contents of gesture recognition, as well as the history of development of gesture recognition technology. Then, the paper does research in the main technology of gesture recognition .The experimental results show that the method can realize 3D gesture recognition in video sequences with real-time and stability, even more; it can get better recognition result.

The paper studies the dancing gestures evaluation method based on images features comparison. The current methods for dancing gestures are according to the people’s vision, which are usually not accurate. Once the dancing is more complex, the conventional methods have the defects of low accuracy. Therefore, this paper proposes an optimized algorithm based on image features comparison for dancing gestures evaluation in which the dancing gestures images are collected. The features in the dancing images are extracted and compared based on the Scale Invariant Feature Transform algorithm (SIFT). The experimental results show that the improved algorithm can increase the accuracy for dancing gestures evaluation greatly.

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

According to the array size,underwater positioning system can be divided into long baseline array, short baseline array and Ultra-short baseline array (USBL). This paper introduces USBL space positioning principle, describes the essence of direction estimation based on the phase measurement , analyses the factors that affect the positioning error, in view of the phase error, this paper introduces the method of improving positioning accuracy from extension formation.

the accurate data mining problem is studied in this paper. With the increasing of data attributes, degree of complexity of the data storage is also increased, resulting in that in data mining process, the complexity of computation is too high, reducing the convergence of the data mining method, thereby reducing the efficiency of data mining. To this end, this paper presents a data mining method based on association rules algorithm. The data is made simplified processing, to obtain the association rules between data which provides the basis for data mining. According to the association rules between the data, the data in line with the minimum support degree is calculated, to achieve accurate data mining. Experimental results show that the proposed algorithm for data mining, can improve mining efficiency, and achieve the desired results.

At present there are many data mining methods. This paper studies the application of rough set method in data mining, mainly on the application of attribute reduction algorithm based on rough set in the data mining rules extraction stage. Rough set in data mining is often used for reduction of knowledge, and thus for the rule extraction. Attribute reduction is one of the core research contents of rough set theory. In this paper, the traditional attribute reduction algorithm based on rough sets is studied and improved, and for large data sets of data mining, a new attribute reduction algorithm is proposed.

By means of word-segmentation technology in TRIP database and each word that appears in a database will be account in detail, a kind of self-constructed category dictionary (SCC-dictionary) in Chinese text classification is proposed. For solving high dimension and sparseness problem exit in vector space model, a four-dimensional feature vector space model (FFVSM) is presented in this paper. With Support Vector Machine (SVM) algorithm, the text classifier is designed. Experimental results show there are two achievements in this paper: first, SCC-dictionary can replace the artificial-written dictionary with the same effect; second, the FFVSM will not only reduce the computing load than high-dimensional feature vector space model, but also keep the precision of classification as 86.87%, recall rate as 95.12%, and F1 value as 90.81%.

In this paper, frame differential method will be used to detect moving targets in a static background video file, and pre-contour can be obtained by binarizing the detected targets . However,, the result are not what was expected, so the expansion and corrosion of mathematical morphology are used to extract the final contour of moving targets. in the progress of dealing with massive data , mathematical morphology is not good enough to achieve the need of the real-time in video surveillance. Considering the dilation and erosion is a kind of parallel processing operations, in order to improve the speed of mathematical morphology operations, this paper offers detailed implementation process of the dilation algorithm for parallel computing on GPU. Experimental results showed that GPU parallel processing on mathematical morphology algorithm faster than the CPU serial processing.

In this paper, the average reprojection geometrical errors on all images of a spatial straight line is taken as the restructuring and optimization target function to ensure the optimal result to be acquired; a spatial straight line is expressed by use of the Plücker coordinates for the proposal of the analytical method of correcting the double linear restriction on the Plücker coordinates of noise-included spatial straight lines; during the optimization process, to ensure parameters that meet double linear restriction, the iteration renewal process is expressed by at least 4 parameters, to increase the precision of restructuring results. Experiments results derived from simulation data and real images have all demonstrated the high efficiency and precision of the algorithm proposed in this paper.