A New Method to Locate the Region of Interest（ROI） of Palmprint

Biometric identification was a kind of identity recognition technology by making use of the human’s unique physiological or behavioral characteristics, it provided a high reliability and stability way for the identification. Global threshold binarization palmprint image is used in this paper, and the bio-morphological methods are used to get the sensitive area of palmprint image’s positioning point, so as to extract the region of interest. The palmprint collection is realized on the FPGA chip, and this kind of collection method uses the DSP Builder toolbox to realize visual programming in Matlab/Simulink and achieve fast modeling and development. The practice proves that this method is simple, flexible and its equipment is portable and fast.     

Study on Image- denoising of Liquid Column in Investment Casting Auto- pouring System

The application of investment casting auto-pouring system can improve the efficiency of manual-pouring system to a certain extent.The judgment of start-stop time depends on the preprocessing of original image collected by the CCD camera.Several methods are presented to denoise the liquid column image.The method of morphological image processing is feasible in theory,and it is important whether to choose the structural element or not.The method of pouring image projection is less affected the image of spure cup.The complexity of image window algorithm is minimal.     

Controllable ion exchange synthesis of Ir/Carbon catalyst

In this paper,a carbon based iridium (Ir) catalyst was prepared by an ion exchange procedure using H2IrCl6 as precursor and a strong basic anion exchange resin as substrate. The Ir/Carbon sample was obtained by carbonizing the precursor. Effects of carbonization parameters such as temperature and time on size and dispersion of iridium crystallite were studied. Samples were prepared at 400 oC and 500 oC to investigate the effect of carbonization temperature. The SEM image of the Ir/Carbon composite shows a hard particle of 0. 2 - 0. 4 mm in diameter,which maintains a spherical shape. The TEM images of the catalyst show that no obvious effects of carbonization temperature or time are observed on the iridium particle size. Calcinated Ir nanoparticles prepared in ion exchange still keep their small particle-sized and narrow-sized distribution. The content of Ir supported on carbon can be well controlled simply by adjusting the relative ratio of Ir to carbon. Such a promising synthesis procedure is a versatile approach that can be extended to the fabrication of some carbon-supported metal catalysts or as a simple,rapid,and highly sensitive method.     

A method of automatic image segmentation for gas bubbles in water

This paper presents an algorithm of automatic bubble image segmentation using the improved ant colony optimization methodology. The ant colony optimization method is a metaheuristic algorithm, and has been applied in many fields. To reveal the versatility and appropriateness of automatic bubble image segmentation, the fuzzy clustering analysis method is employed in ant colony optimization algorithm. Compared with the well-known image feature extraction operators such as SUSAN and Canny, the proposed method can comparatively suitable to extract the gas bubbles image edge features. The experimental results show that the proposed method is effective and reliable, and can achieve satisfactory image edge extraction effect.     

A systematic method based on statistical pattern recognition for estimating product quality on-line

To avoid the complexity of building mechanistic models by studying the inner nature of the object, a systematic method based on statistical pattern recognition is developed in order to estimate the product quality on-line. The mapping relationship between a feature space and a product quality space can be built by using regression analysis, and in applying clustering analysis the product quality space can be partitioned automatically. Eventually, estimating product quality on-line can be accomplished by sorting the mapped data in the partitioned quality space. A concrete problem is proposed which has a relatively small ratio of training data to input variables. By implementing the method mentioned above, a satisfying result has been achieved. Furthermore, the further question about choosing suitable mapping methods is briefly discussed.     

Digital image correlation based high-speed crack tip locating method and its application

Based on a digital image correlation (DIC) method with the measurements of a high speed crack''s displacement and strain fields, a technique to accurately and automatically locate its crack tip has been developed. The crack tip is identified by finding the abrupt jump on the opening (or dislocation) curve of a point on the trace of the crack propagation, while the opening is measured through a virtual extensometer technique and the abrupt jump is identified by finding the peak on the curve. The method was verified using a specially designed experiment and applied to measure the critical crack tip opening angle of a rock sample. Because the involvement of analytical models has been avoided and then the good performance could be ensured for low resolution speckle images, this technique is expected to be very useful in the quantitative study of high speed cracks in experiments using high speed cameras.     

On the robustness of EEG tensor completion methods

During the acquisition of electroencephalographic(EEG) signals, data may be missing or corrupted by noise and artifacts. To reconstruct the incomplete data, EEG signals are firstly converted into a three-order tensor(multi-dimensional data) of shape time × channel × trial. Then, the missing data can be efficiently recovered by applying a tensor completion method(TCM).However, there is not a unique way to organize channels and trials in a tensor, and different numbers of channels are available depending on the EEG setting used, which may affect the quality of the tensor completion results. The main goal of this paper is to evaluate the robustness of EEG completion methods with several designed parameters such as the ordering of channels and trials, the number of channels, and the amount of missing data. In this work, the results of completing missing data by several TCMs were compared. To emulate different scenarios of missing data, three different patterns of missing data were designed.Firstly, the amount of missing data on completion effects was analyzed, including the time lengths of missing data and the number of channels or trials affected by missing data. Secondly, the numerical stability of the completion methods was analyzed by shuffling the indices along channels or trials in the EEG data tensor. Finally, the way that the number of electrodes of EEG tensors influences completion effects was assessed by changing the number of channels. Among all the applied TCMs, the simultaneous tensor decomposition and completion(STDC) method achieves the best performance in providing stable results when the amount of missing data or the electrode number of EEG tensors is changed. In other words, STDC proves to be an excellent choice of TCM, since permutations of trials or channels have almost no influence on the complete results. The STDC method can efficiently complete the missing EEG signals. The designed simulations can be regarded as a procedure to validate whether or not a completion method is useful enough to complete EEG signals.     

Methods for optical phase retardation measurement:A review

Optical-phase-retardation elements are widely used in many fields.Accurate measurement of their phase retardation is crucial to the practical effect of the element’s processing and application.The development and present situation of the methods for optical phase retardation measurement are reviewed,with the wave plate,the most typical phase-retardation element,as an example.The latest research progress in this field is introduced;the principles and characteristics of individual measurement method are summarized and discussed.Three new methods based on laser frequency splitting or laser feedback are presented in detail,in which the laser is not only regarded as a light source but also plays a role of sensor.Moreover,no standard wave plates are needed and arbitrary phase retardation can be measured.Traceability,high precision and high repeatability are achieved as well.     

Numerical prediction of the incremental melting and solidification process

A mathematical formulation is applied to represent the phenomena in the incremental melting and solidification process (IMSP), and the temperature and electromagnetic fields and the depth of steel liquid phase are calculated by a finite difference technique using the control volume method. The result shows that the predicted values are in good agreement with the observations. In accordance with the calculated values for different kinds of materials and different size of molds, the technological parameter of the IMS process such as the power supply and the descending speed rate can be determined.     

Traffic sign recognition algorithm based on shape signature and dual-tree complex wavelet transform

A novel traffic sign recognition system is presented in this work. Firstly, the color segmentation and shape classifier based on signature feature of region are used to detect traffic signs in input video sequences. Secondly, traffic sign color-image is preprocessed with gray scaling, and normalized to 64×64 size. Then, image features could be obtained by four levels DT-CWT images. Thirdly, 2DICA and nearest neighbor classifier are united to recognize traffic signs. The whole recognition algorithm is implemented for classification of 50 categories of traffic signs and its recognition accuracy reaches 90%. Comparing image representation DT-CWT with the well-established image representation like template, Gabor, and 2DICA with feature selection techniques such as PCA, LPP, 2DPCA at the same time, the results show that combination method of DT-CWT and 2DICA is useful in traffic signs recognition. Experimental results indicate that the proposed algorithm is robust, effective and accurate.     

An Introduction to Convex Optimization Theory in Communication Signals Recognition

In this paper, convex optimization theory is introduced into the recognition of communication signals. The detailed content contains three parts. The first part gives a survey of basic concepts, main technology and recognition model of convex optimization theory. Special emphasis is placed on how to set up the new recognition model of communication signals with multisensor reports. The second part gives the solution method of the recognition model, which is called Logarithmic Penalty Barrier Function. The last part gives several numeric simulations, in contrast to D-S evidence inference method, this new method can also generate reasonable recognition results. Moreover, this new method can deal with the form of sensor reports which is more general than that allowed by the D-S evidence inference method, and it has much lower computation complexity than that of D-S evidence inference method. In addition, this new method has better recognition result, stronger anti-interference and robustness. Therefore, the convex optimization methods can be widely used in the recognition of communication signals.     

Super-Resolution Image Reconstruction Based on an Improved Maximum a Posteriori Algorithm

A maximum a posteriori (MAP) algorithm is proposed to improve the accuracy of super resolution (SR) reconstruction in traditional methods.The algorithm applies both joints image registration and SR reconstruction in the framework,but separates them in the process of iteratiion.Firstly,we estimate the shifting parameters through two low resolution (LR) images and use the parameters to reconstruct initial HR images.Then,we update the shifting parameters using HR images.The aforementioned steps are repeated until the ideal HR images are obtained.The metrics such as PSNR and SSIM are used to fully evaluate the quality of the reconstructed image.Experimental results indicate that the proposed method can enhance image resolution efficiently.     

Three-dimensional motion parameters estimation from stereo image sequences based on infrared reflective markers

In this paper,an innovative 3D motion parameters estimation method from stereo image sequences based on infrared(IR) reflective markers is presented.It was assumed that two high speed CCD cameras had been calibrated previously.The method consists of the following steps:1) the coordinate of several markers and depth map for each stereo pair was determined from the sequences of stereo images by relations of markers’ coordinate the correspondence between markers was established,2) the 3D motion parameters of the target was computed based upon the matched markers’ coordinate,and 3) translated 3D motion parameters estimation into the problem of least square according to the movement model of the object to be measured.Without using line,curve or corner correspondence,this method can calculate the depth of these markers feature easily and quickly in contrast to traditional approaches.The two CCD cameras work on 200 f/s,and each processing cost time is about 3 ms.It was found that,by using several markers and a large number of stereo images,this method can improve the computational speed,robustness and numerical accuracy of the motion parameters in comparison with traditional methods.The virtual simulation experiment was conducted using synthesized stereo image sequences based on 6-DOF motion platform and the experimental results proved the validity of our approach and showed that the translation and rotation precision is up to 0.1 mm and 0.1°.     

Study of “3-Step Mining” Subsidence Control in Coal Mining Under Buildings

Mining subsidence damage is the main factor of restricting coal mining under buildings. To control or ease effectively the degree of mining subsidence and deformation is essential to resolve this problem. Through analyzing both advantages and disadvantages of some technologies such as mining with stowing, partial extraction and grouting in separated beds of overburden, we used the principle of load replacement and propose a “3-step mining” method, a new pattern of controlling mining subsidence, which consists of： strip mining, i.e. grouting to fill and consolidate the caving zone and retained strip pillar mining. The mechanism of controlling mining subsidence by using the “3-step mining” pattern is analyzed. The effect of the control is numerically simulated. The preliminary analysis shows that the “3-step mining” can effectively control ground subsidence and deformation. By using this method, the ground subsidence factor can be controlled to a value of about 0.25. Coal recovery can reach 80%-90%. Coal mining without removing surface buildins can be realized and the economic loss resultin from round subsidence can be greatly reduced.     

Lighting Model of the Real World in Augmented Reality

Construction of a lighting model of the real world is one of the critical aims in an augmented reality (AR) system. The theory of lighting modeling used in computer graphics(CG) is applied in this study. The position of the real light-source is first conjectured from light and shade of the registration image element by element using a ray tracking algorithm. Then the virtual light-source and virtual fiducial are constructed in the CG environment, in which, the Phong model is used to draw the light effect. By comparing the CG scene with the real image, one can modify the parameters of the lighting model over and over again, until the lighting effect of the CG scene is close enough to that of the real image. It is proved that this method works well in the indoor AR system. The method can be used feasibly in most applications with some improvements.     

Building of road boundary map based on laser radar

A method for road boundary detection and tracking using laser ladar with respect to a vehicle’s local coordinates is proposed.It can be applied to different types of road conditions,such as roads with or without curbs,having relatively rough road surface and with obstacles on road surface.In the method,some line segments are extracted after a series of preprocessing on range data.The extracted line segments are combined and further selected.They are then united to match the road models and generate the road boundary points which are tracked by Kalman filter.Then the obtained road boundary points are transformed to build a precise vector map by least squares fitting algorithm.These fitted line segments represent road boundary vectors.The vector map is precise enough to provide ample road information such as the orientation of road,the road width and the passable road region.Finally,extensive experiments conducted in urban and semi-urban environment demonstrate the robustness,effectiveness and viability of the proposed method.     

Time series ground subsidence inversion in mining area based on CRInSAR and PSInSAR integration

The subsidence of the mining area was monitored by analyzing the phase of permanent scatters （PS） which maintained high coherence in magnitude of SAR images.A hew method of spatial unwrapping was presented which used the subsidence rates calculated on comer reflector （CR） points as constraints for PS network to perform the spatial unwrapping using the parametric adjustment method.The algorithm achieved the integration of CR data and PSInSAR algorithm.The colliery dense distributed area around Baisha reservoir was chosen as the study area in the experiment.The time series of subsidence from February in 2007 to February in 2010 is successfully inversed by using the periodic function to simulate the linear and nonlinear components of the deformation.The simulation results show that the accuracy can be ± 2.1 mm with the leveling data being used as the external validation data.