Cluster synchronization of a class of multi-agent systems with a bipartite graph topology

This paper investigates cluster synchronization of a class of multi-agent systems with a directed bipartite graph topology,and presents a number of new results by using the neighbor’s rules for the following two cases:I)there is competition among the agents of diferent clusters,and II)there are both competition and cooperation among the agents.Firstly,for case I),a linear control protocol is designed for cluster synchronization of multi-agent systems,and a method is presented to determine the final state with the initial conditions based on state-space decomposition.Secondly,we study case II),and design a control protocol based on the information of neighbors and that of two-hop neighbors(that is,neighbors’neighbors).Finally,two examples are studied by using our presented results.The study of illustrative examples with simulations shows that our results as well as designed control protocols work very well in studying the cluster synchronization of this class of multi-agent systems.     

Unsupervised image segmentation based on MRFs and graph cuts

Markov random fields （MRFs） can be used for a wide variety of vision problems. In this paper we will propose a Markov random field （MRF） image segmentation model. The theoretical framework is based on Bayesian estimation via the energy optimization. Graph cuts have emerged as a powerful optimization technique for minimizing energy functions that arise in low-level vision problem. The theorem of Ford and Fulkerson states that min-cut and max-flow problems are equivalent. So, the minimum s/t cut problem can be solved by finding a maximum flow from the source s to the sink t. we adopt a new min-cut/max-flow algorithm which belongs to the group of algorithms based on augmenting paths. We propose a parameter estimation method using expectation maximization （EM） algorithm. We also choose Gaussian mixture model as our image model and model the density associated with one of image segments （or classes） as a multivariate Gaussian distribution. Characteristic features related to the information in color, texture and position are extracted for each pixel. Experimental results will be provided to illustrate the performance of our method.     

Improving extraction of watermarks in color attacked watermarked images

A new approach for modeling color attacks of RGB-color watermarked images is presented in this paper. We have used a based interpolation watermarking algorithm and supposed that the attacks are simulated by a scaling of the colors followed by a translation. Then give bounds for the extracted watermark depending on the original image, the watermark and the attack. Different attacks like LSB, embedding another watermark, Stirmark have been simulated and the quality of the extracted watermark is discussed in each case.     

A semantic web methodology for situation-aware curative food service recommendation system

Recently curative food is becoming more popular, as more people realize its benefits. Based on the theory of Chinese medicine, food itself is medicine. The curative food which is an ideal nutritious food can help to loss weight, increase immunity and is also good for curative effects in patients. In this paper, we propose a new Curative Food Service （CFS） recommendation system, the designed Situation-aware Curative Food Service Recommendation System （SCFSRS）, which provides the cooperation web-based platform for all related Mobile Users （MUs） and Curative Food Service Providers （CFSPs）, could strengthen the ability of CFS suggestion. SCFSRS is a five-tier system composed of the MUs, UDDI Registries （UDDIRs）, CFSPs, Curative Food Services Server （CFSS）, and Database Server （DS）.     

Local thresholding with adaptive window shrinkage in the contourlet domain for image denoising

Threshold selection is a challenging job for the image denoising in the contourlet domain. In this paper, a new local threshold with adaptive window shrinkage is proposed. According to the anisotropic energy clusters in contourlet subbands, local adaptive elliptic windows are introduced to determine the neighboring coefficients with strong dependencies for each coefficient. Utilizing the maximum likelihood estimator within the adaptive window, the signal variance is estimated from the noisy neighboring coefficients. Based on the signal variance estimation, the new threshold is obtained in the Bayesian framework. Since it makes full use of the captured directional information of images, the threshold extends to the anisotropic spatial adaptability and behaves reliably. Simulation experiments show that the new method exhibits better performance than other outstanding wavelet and contourlet denoising schemes obviously, both in the PSNR value and the visual appearance.     

Image decomposition on the basis of an inverse pyramid with 3-layer neural networks

The contemporary information technologies and Internet impose high requirements on the image compression efficiency. Great number of methods for information redundancy reduction had already been developed, which are based on the image processing in the spatial or spectrum domain. Other methods for image compression use some kinds of neural networks. In spite of their potentialities, the methods from the last group do not offer high compression efficiency. New adaptive method for image decomposition on the basis of an inverse pyramid with neural networks is presented in this paper. The processed image is divided in blocks and then each is compressed in the space of the hidden layers of 3-layer BPNNs, which build the so-called inverse difference pyramid. The results of the new method modeling are presented for sequence of static images in comparison with results for single images from the same group.     

A New Medical Image Enhancement Based on Human Visual Characteristics

Study of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact effectively to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest （ROI） is segmented; then the Un-sharp Masking （USM） is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.     

Color image recognition method based on the prewitt operator

A method of extracting the target image edge combined with digital image recognition technology is discussed. The prewitt algorithm is employed to detect the edge boundary of the given color image and the quadtree segmentation technique is employed to cut down the storage cost of identification codes. The edge information of color images is exploited to design the identification codes. This method can be used to verify the integrity of the color images by detecting the modified areas of the color images. The experiment results show that the method can locate and extract the modified areas of the color images, operate easily and has well practicability.     

Image geometry and radio metrics correction and optimization in image mosaic

In image guided navigation, due to radiometric and geometric distortions of images from photography, it can mislead the content of the image, image series are finally converted into the same coordinate system. Based on the analysis of correction algorithm, a much better one is presented, which is proved to be effective in the correction of radiometric image distortion. A theory using image local maximum modules, got by wavelet transform, as image feature, is promoted. Using image mosaic technique based on multi-resolution analysis, redundancies between images are eliminated. The whole image produced at last is a much bigger one without seam and distortion.     

Application of data warehouse in power transformer diagnosis system

Electric power companies have accumulated huge amounts of historical fault data of power transformer after many years operation, but the decision-makers have not been greatly supported because of the limitation of knowledge and can not make decision for transformer condition assessment. A real power corporation is selected as the research background. Based on analyzing and reorganizing the various existing data sources, the power transformer fault information data warehouse is constructed and snowflake mode cubes for multi-dimension data are established. By using Processing） and data mining analyzing and inquiring data OLAP（On-Line Analysis technology, forecasting load, warehouse are realized from different point view and multi-layers, including rolling up, drilling down, slicing, dicing and rotating etc.. Moreover, this paper proposes a novel transformer fault data mining system based on data warehouse. Finally, bayes network of fault patterns are obtained, which can greatly help the decision-making for the system operating and management. The results show that transformer fault diagnosing system based on data warehouse technology can provide efficient decision supporting.     

Segmentation methods of fruit image based on color difference

Fruit image segmentation issue on color difference between mature fruits and backgrounds under natural illumination condition is an important and difficult content of fruit-harvesting robot vision. Some studies concerning fruit image segmentation have been presented in the last few years. However, these studies are focused on particular fruit and different from segmentation results. In this paper, four kinds of segmentation methods are presented and applied into fruit image segmentation. The tests show that these methods can segment successful several kinds of fruits image, such as apple, tomato, strawberry, persimmon and orange. Dynamic threshold segmentation method has better performance and least cost time than extended Otsu method, improved Otsu combined with genetic arithmetic and adaptive segmentation method based on LVQ network. Meanwhile, it has satisfactory effect upon fruit image under natural illumination condition. Adaptive segmentation method based on LVQ network can only be applied into balanced color instance of particular fruit, and it isn＇t adapt to be applied into real-time occasion because of high cost time.     

Audio recording of rock/metal music using personal computers

Personal computers and their relevant technologies have been widely used by artists and musicians to create and record their own music and electroacoustic compositions. ＂Laptoppers＂ are famous for using their laptops for their dance/electronic beats and music. A genre that has not relied on the use of PCs for the production of its music is rock/heavy metal, since bands of these genres usually book recording studio time where professionals take on the task of the production using expensive equipment. This study shows that in today＇s day and age, and with the software and hardware currently available, it is possible for rock/metal artists to use their PC to record and produce their own CD successfully and at an extremely competitive cost. The effort＇s of a rock band that does just this is followed from the beginning and the results of their CD production and song successes is presented. The article also serves as a ＂HowTo＂ guide that bands on a low budget can follow to make good quality demo CDs and enter the music business industry.     

Halftoning based algorithms for image hiding

Digital halftoning is an important process to convert a continuous-tone image into a binary image with pure black and white pixels. This process is necessary when printing a monochrome or color image by a printer with limited number of ink colors. The main contribution of this paper is to present a halftoning method that conceals a binary image into two binary images. More specifically, three distinct gray scale images are given, such that one of them should be hidden in the other two gray scale images. Our halftoning method generates three binary images that reproduce the tone of the corresponding original three gray scale images. Quite surprisingly, the secret binary image can be seen by overlapping the other two binary images. In other words, the secret binary image is hidden in two public binary images. Also, it is very hard to guess the secret images using only one of the two public images, and both of these two public images are necessary to get the secret image. Another contribution of this paper is to extend our halftoning method to hide one image and more than one image into more than two images. The resulting images show that our halftoning method hides and recovers the original images. Hence, our halftoning technique can be used for watermarking as well as amusement purpose.     

Research and realization of panoramic space generation technology

This paper proposed a generation technology of virtual panoramic space. This technology captured multi-channel video images from several camera heads, combined these images real-timely into 360 degree panoramic images and composed a virtual panoramic space with a series of panoramic images.     

Content-based facial image authentication via statistic features

A statistic approach for facial image authentication is proposed. The typical model of digital signature generation and facial image authenticating is discussed firstly. Then the interesting region of facial image is extracted by a set of haar-like features. To prepare enough training samples, a sample enlarging method based power low transformation （PLT） is proposed. The statistic feature of a facial image is extracted by calculating the coefficients of it＇s projection onto a subspace trained offiine by the enlarged sample set. The experimental results demonstrated the capability to distinguish the content-preserving operations and the malicious operations.     

The existence and synchronization properties of symmetric fix-free codes

Fix-free codes are a type of variable length codes with both prefix-free and suffix-free properties, and there are two types of fix-free codes： symmetric fix-free codes and asymmetric fix-free codes. In this paper, we mainly discuss symmetric fix-free codes. First, the existence of symmetric fix-free codes is studied in detail, and some necessary and sufficient conditions are proposed. We also discuss the problem of achieving synchronization of symmetric fix-free codes, which is important in application. We then establish a scheme with synchronizing codewords to resolve this problem.     

Rescheduling to minimize total completion time under a limit on the makespan of the original jobs

We consider the rescheduling problems arising when two agents, each with a set of nonpreemptive jobs, compete to perform their respective jobs on a common processing resource. Each agent wants to minimize a certain objective function, which depends on the completion time of its jobs only. In this paper, we consider the two agents rescheduling problems for jobs on a single machine to minimize total completion time under a limit on the makespan of the original jobs. We show that the considered problems can be solved in polynomial time or pseudopolynomial time.