Applied Mechanics and Materials Vols. 668-669

Abstract: As for MEMS Micro machined accelerometer, biases characteristic always varies with temperature fluctuations. Through establishing the error model between the MEMS accelerometer biases and the temperature variation in the temperature range of-20 °C ~ 60 °C, studying on the bias changed with thermal variation of MEMS accelerometer, and the test results show that MEMS accelerometer bias caused by temperature change have decreased from more than 5mg to lessen than 1mg before and after compensation. Also based on the temperature error model of the MEMS accelerometer bias in static and dynamic condition, the whole temperature characteristics have been improved to some extent, which would improve the precision in the inertial navigation systems.

Abstract: This paper analyses the motion of animation with the methods of picking key points and predicting motion trace based on the particle filter for discrete particle track prediction theory. The behavior model has been built for the already existing animation character. During the research, the thesis realized using existed animation motion trace model to drive a similar figure and create a new animation.

Abstract: Aiming at the problem of face tracking under rapid moving process, a fast and robust tracking method is proposed. The possible position of face detected by the Camshift algorithm in the next frame is predicted by the square-root cubature Kalman filte (SCKF). Then, the localization and tracking of face are got frames by frames. The experimental results show that: the use of SCKF to solve the nonlinear effect caused by non-uniform motion of face and overcome the target loss problem of the linear Kalman algorithm. The proposed method greatly improves the tracking accuracy of face in the process of rapid movement.

Abstract: In this paper, feature extraction algorithm based on spherical perspective projection model for the matching fisheye image is proposed. The fisheye image is mapped to the image plane through spherical mapping. Then the diffusion equation is formed by convolution of the image projection and spherical Gaussian function. The feature points of image are extracted based on the SIFT at the scale of spherical correlation function. Compared with SURF(Speeded Up Robust Features), more feature points in a shorter time are obtained.

Abstract: As a novel MGA (Multiscale Geometric Analysis) tool, shearlet is equipped with a rich mathematical structure similar to wavelet. In this paper, a novel image fusion method using Non-subsampled Shearlet Transform is proposed. First, the source images are decomposed into low-pass and high-pass subbands using NSST. Second, the high-pass subbands coefficients of the images are fused according to the average gradient. Third, the low-pass subbands coefficients of the images are fused by the weighted regional entropy. Finally, the image is reconstructed by the inverse non-subsampled shearlet transform. In the method, two sets of source images and five objective parameters are used to test the algorithm. The experimental results show that the proposed method is better than the conventional DWT-based and NSCT-based methods.

Abstract: The probabilistic distribution of Airport arrival and departure delays over a selected period of eight months was analyzed using an optimal Generalized Extreme Value (GEV) model in this paper. It is anticipated that quantitative stochastic characterizations of delay data out of our work would improve demand predictions in air traffic flow management systems. Analysis and verification through application of Beijing Capital International Airport’s history flight delay data demonstrate better Goodness of Fit of our optimal GEV based model.

Abstract: This paper firstly studies the texture features. We construct a gray-difference primitive co-occurrence matrix to extract texture features by combining statistical methods with structural ones. The experiment results show that the features of the gray-difference primitive co-occurrence matrix are more delicate than the traditional gray co-occurrence matrix.

Abstract: An improved blind deconvolution algorithm has been proposed to tackle the image blurring caused by movement. Firstly, take the model to analyze the blurred image and identify the high-frequency of the blurred image through the reasonable pre-estimation of blind kernel function. Then, further estimate the blurring matrix K by the use of the high-frequency while the high-frequency of the blurred image and the accuracy of the blurred image matrix have been improved gradually through normalized iteration. Finally, the clear image has been gained by the use of blind matrix deconvolution. Experimental results show that by the use of this algorithm the image has better subjective visual effect. The proposed algorithm has better restoration effect on the fused motion blurred image and the natural camera motion blurred image.

Abstract: Automatic white balance algorithm (AWB) is significant for color temperature restoration of digital imaging system. According to the limitations and disadvantages of existing traditional white balance methods, in this paper a new AWB algorithm for airborne camera is proposed. Using RGB and histogram information divide the input image into different color character regions; according to the color richness level, adopt different white balance algorithms to achieve chromatic aberration adjustment. Experiment results show the effectiveness of the proposed AWB algorithm for airborne camera.

Abstract: Digital camera is widely used in the data collection of objective and background in the field of pattern design and supervisory controlling. However, the color in digital photo copied from camera is not in accord with the actual color of objective, which affects the accuracy of design pattern. The polynomial regression algorithm is widely used in color reproduction of image input and output area. The accuracy of color reproduction is related to the different order. Therefore, the field experiment is developed. The application indicates that the performance of four order polynomial regression color reproduction is the best algorithms and it can be used in color reproduction.