Adaptive polarization i mage fusion based on regional energy dynamic weighted average

According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations,most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

Parameter recognition for defocus blur image using cepstrum analysis

Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the point spread function(PSF)can be identified conveniently in the frequency field for peopleby manual means rather than for computer.This paper introduces a practical method for computer to esti-mate the defocus blur parameter in cepstrum area.Fourier transform plays an intermediate role in the pathto cepstrum domain.We suggest a weighted adjustment operation in the frequency domain and then con-vert it to the cepstrum field to increase the accuracy of recognition.

New Measurement of Swaying Quantity and Multi-barrel Parallelism for Rocket Launcher

By analyzing the deficiencies of the method, a measurement system with the technologies of photoelectricity, laser and digital image processing to synthetically measure these two parameters has been developed. A traditional method to measure the swaying quantity and multi-barrel parallelism of rocket launcher is introduced. Meanwhile, the principle, executive plan and the accuracy analysis are also presented. The photoelectric measurement system has been applied in the swaying quantity and multi-barrel parallelism measurement for Φ122 mm and Φ302 mm rocket launcher. The metrical errors are both 16^th.

Measurement of 3-D motion parameters of jacket launch based on stereo image sequences

To make sure that the process of jacket launch occurs in a seml-controlled manner, this paper deals with measurement of kinematic parameters of jacket launch using stereo vision and motion analysis. The system captured stereo image sequences by two separate CCD cameras, and then rebuilt 3D coordinates of the feature points to analyze the jacket launch motion. The possibility of combining stereo vision and motion analysis for measurement was examined. Resuhs by experiments using scale model of jacket confirm the theoretical data.

Classification of surface EMG signal with fractal dimension

Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). After the high frequency noise is filtered from surface EMG signal by a low-pass filter, fractal di-mension is calculated from the filtered surface EMG signal. The results showed that the fractal dimensions of filtered FS surface EMG signals and those of filtered FP surface EMG signals distribute in two different regions, so the fractal dimensions can rep-resent different patterns of surface EMG signals.

Smooth feature line detection for meshes

In this paper the authors present a novel semi-automatic feature line detection technique for meshes. Taking into account the distance and orientation between two vertices on meshes and the curvature information of vertices, they first find an initial feature line which connects some user-specified vertices on meshes; then parameterize the “feature strip” surrounding the feature line onto a planar domain using a vertex flattening technique; and refine the flattened feature strip using the 2D snakes approach to make the feature line smoother and more accurate; lastly they get the feature line by mapping the refined line back to the original meshes. Experimental results showed that their method can extract the feature line rapidly and precisely. As an ap- plication, they propose a mesh decomposition method based on the detected feature line.

Study on the forecast method for underground coal mine

At present,coal mine fires were forecasted with some temperature,smog,CO,CO_2,etc,however,this method can't meet the requirements for safe production of coalmines in monitoring accuracy and validity.Overcoming these problems of foregone moni-toring methods,using multi-parameters which include fire image,smog,CO,CO_2,O_2,etc,the paper put forward a synthetical analysis monitor with advanced technology of neuralnetwork.The research and application of this method has significance in theory and prac-tical value for coal mine fire forecast.