Aiming at the threat of active laser detection system for electro-optical devices based on “cat-eye” effect in battle field, a new method is put forward to eliminate “cat-eye” effect by using circular holes array’s intensity modulation. Based on the principles of single hole’s diffraction imaging process and spatial translation effect, intensity distribution characteristic of far-field Fraunhofer diffraction for circular holes array is deduced and then simulated. The stealth effect of “cat-eye” target is proved by experimental method by using circular holes array without changing the optical structure of electro-optical device. The results show that the echo intensity of “cat-eye” target can be modulated by circular holes array, which causes echo energy’s loss, while the effect on imaging quality is finite. “Cat-eye” target’s stealth effect is remarkable by this method.

In order to improve the ground pixel resolution, the image motion compensation device system should be designed to compensate image motion of the CCD plane in the area scan color CCD camera. An image motion compensation mechanism is designed based on analysis of several kinds of image motion compensation methods and discussion on image motion compensation device. Constant-diameter conjugate cam is used to translate the rotation to the line movement. It has the advantages of simple transmission chain and microscopic operation and can reduce the transmission error effectively. The factors that affect the accuracy of image motion compensation are studied and equivalent residual image motions of the compensating system are measured. The measuring results show that the focusing mechanism has a high precision and the error is less than 600 μm/s. Clear color imagine in aerial tests proves that the camera’s technical parameters can meet using demands.

The star sensor is a high-precision attitude sensitive measuring instruments, which determine spacecraft attitude by detecting different positions on the celestial sphere. Star camera is the imaging system of star sensor. Despite the rapid development of CMOS technology, in science class imaging, especially, CCD camera still has a great advantage in applications of star sensor. The purpose of this study is to increase the performance and data update frequency of CCD camera for star sensor. The working principle of CCD is described, the CCD sensor detection sensitivity is analyzed, and the design of CCD star camera is discussed based on TH7888A. Performance of the camera can be validated through imaging and detection experiments. By analyzing the experimental images, it is found that the camera can detect Mv6 stars in 60 ms integration time through a given the small optical system. The camera’s image data update frequency can reach 10 frame/s and meets the rapid imaging requirements in short integration time.

Compared with the traditional aerophotogrammetry, the Unmanned Aerial Vehicles (UAV) images have the problems of bigger and more complex geometric distortion and because of the large photographic scale, the texture of images changes little in some features. These factors lead more difficult to matching UAV images, and increase the number of mismatch cognominal points. At first, according to the Harris operator, extract and match feature points. A method for detecting and eliminate the mismatch points was proposed based on the polygon matching. The method considers the reliability of cognominal points matching from distance, angle and weight. Through the experiment, the feasibilitynumber of mismatch points, operation speed and matching accuracy were calculated out in different areas, and the of the method was verified.

The large plain benchmark instrument is indispensable to assemblage of the large caliber space camera optical system, and the plain benchmark instrument’s caliber is required to be bigger and bigger because the caliber of camera optical system is bigger and bigger. In order to meet the requirements of the integrated precision of the mirror segment used for big space camera, selection of the materials of reflected mirror and supporting structure was introduced, and the design method of the flexible supporting structure of the mirror was proposed, which is analyzed and optimized through CAD/CAE engineering analysis software. Furthermore, a sort of reasonable flexible supporting structure for reflected mirror is optimized by means of Finite Element Method (FEM).

The velocities of particles in Electrorheological (ER) fluids were measured by laser speckle velocimetry. It was verified that laser speckles could be formed by illuminating laser beam on the starch ER fluids. The speckle patterns was recorded with high speed CCD camera, and the speckle patterns sequences with short time intervals was obtained by intercepting laser speckle video. Velocities parallel to the direction of electric field and that perpendicular to the direction of electric field were obtained by processing the two consecutive speckle patterns. The experimental results show that the velocities of particles decreases oscillatorily with time. Furthermore, there is a critical electric field and a critical sample concentration. When it is lower than this critical electric field (particle concentration), the mean particle velocity increases; otherwise, it decreased.

A new image measurement and calculating method was proposed to improve the measurement accuracy and adaptability of auto lensmeter. Firstly, 16 dots infrared image driven by constant pulse current was received with CCD. Secondly，image was processed by high speed CPU system, and binary image was divided up by CPU system. Finally, we can acquire the diopter parameter of glass by least square method. The experiment was carried out using the standard glass and the glass with nick and dirt. Compared with 4 dots method, results show that the measurement errors are less than ±0.06 D which was minimum error of diopter prescribed by National Metrology Bureau. In addition，the accuracy of the glass with nick and dirt was improved obviously, and adaptability of environment was also enhanced.

A method based on Support Vector Machine (SVM) classification algorithm to detect the defects of oil-seal surface was put forward, in which the defective area and non-defective area were treated as two different textures and were sampled respectively to be learned for classification by SVM. Testing areas were cut out of the preprocessed images of oil-sea different sections, and different feature parameters were selected according to the characteristics of various defects in oil-seal testing area on the base of image analysis. SVM recognition model was established by application of Radial Basis Function (RBF), and the parameters of RBF were optimized through cross validation experiments. The results showed that the proposed approach was characterized by low cost, high reliability, excellent generalization, and easy on-line implementation and so on, and could be applied for defect detection of various products.

Aiming at the difficulty of single camera system calibration used in cylinder-shaped large forging parts measurement, a new self-calibration method was proposed based on self constraint of the target cylinder-shaped object; the inner and outer parameters of the measurement system were achieved from a single image. Firstly, taking advantage of the rotation characteristics of the cylinder-shaped large forging parts and the supporting shaft, inner parameter constraint equations were established based on circular points and epipolar constraint derived from images of cross sections. And then the full inner matrix of the measurement system was solved using the constraint equations. Secondly, the outer parameter equations were established using the image of rotation axis and cross sections as well as the inner parameters, and the outer parameters were achieved. Experimental results verified the convenience and effectiveness of the proposed method.

Defect inspections of Compact Camera Module (CCM) are made mainly by human inspectors. For improving the efficiency and precision, it’s very necessary to develop an automatic inspection system for CCM. It can check lens focus status and inspect defects including white defect, black defect, line defect, color defect, and dim defect in manufacturing process. It has a complex programmable logic device, and the camera link and the frame grabber are used to transfer and store images to PC. Various image processing algorithms are developed to analyze the captured image from each test chart and to find and verify the defects of camera modules. The experimental results show that the proposed system is able to reliably inspect various types of defects with high precision and high speed in real manufacturing condition.

Because of focus changing when TFT inspection device performing auto focus, the resolution of device will inevitably changes. So there is a need to offer a fast estimation method for device’s actual resolution. Since total resolution is the product of camera resolution and lens resolution, at first, camera contrast limit is set up based on all kinds of noise model. Then, LCD white and black bar fringe are used whose frequency changes gradually to estimate lens MTF degeneration. Finally, through relationship between resolution and contrast, the spatial cut through frequency can be calculated by differentiating imaging system’s light dark blur smallest differences at highest camera contrast distinguish condition. Experimental results indicates that when using optic inspection device to examine cell phone background light panel's defects, article's method estimates the actual resolution less than 17 μm , in contrast test, the calibrated sample defects exceeds 17 μm can be photographed clearly using device. The results prove the effectiveness of the proposed method.

Grain shape is an important feature, which determines the grain quality and yield. Traditional manual determination of grain shape is time-consuming, laborious and subjective. A system for automatically determining the grain shape is presented based on a line-scan camera and a coveyor belt. In order to improve the grain shape determination efficiency, parallel processing technique based on Graphics Processing Unit (GPU) is used. On the basis of Compute Unified Device Architecture (CUDA), the grain shape determination algorithm is optimized. The experiment result shows that the GPU-based accelerated algorithm can achieve a good effect on the measurement efficiency. When the number of grain in an image is approximately 2 000, the optimized algorithm gets a speedup of more than 400 times. Moreover, as the quantity of kernels in the images gets larger, the performance of the grain shape determination algorithm is improved more significantly.

Referring to equidistant projection fisheye imaging model, self-calibration bundle adjustment for lunar rover hazard avoidance cameras are carried out by using the methods of calibration fields. The interior parameters and relative of exterior parameters of hazard avoidance cameras are calibrated. Using the obtained calibration parameters, the three-dimensional coordinates of the photogrammetry targets are recovered to get the three-dimensional coordinates of the targets hazard avoidance cameras coordinate system. Compare this three-dimensional coordinates with the known three-dimensional coordinates, and assess the calibration accuracy of hazard avoidance cameras by the comparative bias results. The experiment demonstrates the effectiveness of the calibration parameter models and the calibration method for the lunar rover hazard avoidance cameras.

Laser tracker distance measurement accuracy depends on the accuracy of laser Interferometer Measurement(IFM) and Laser Absolute Distance measurement (ADM). Based on the current technology, IFM measurement accuracy is much higher than ADM measurement accuracy. So the ADM measurement error needs to be compensated in order to improve laser tracker measurement accuracy. The compensation method of cubic spline function and linear function is compared and analyzed. The results show that the residual error of cubic spline function compasation method is 0.007 mm, which is much better than that of linear function method (0.029 mm). The verification points also show the same result. The conclusion is drawn that cubic spline function can be used to better correct ADM error of laser tracker.

The principle of the random ball test technology is introduced. There are two types of random ball test technologies. One is called static method; the other is called dynamic method. The relation between calibrating error and the number of measurements in these two methods is analyzed separately. Based on statistics and reasonable assumption, the analysis shows that static method is one of the special dynamic methods. In both of these two methods, the calibrating error drops off as N-1/2 with the number of measurements increases. The experiment of random ball test is done using dynamic method. The experiment result shows that the calibrating error drops off as N-1/2 with the number of measurements increasing approximately.

In electronic speckle shearing test systems, the shear has a big impact on measurement accuracy, sensitivity, and the fringe contrast. This article introduces the principle of electronic speckle shearing interferometry and the relationship among shear and measuring accuracy, sensitivity, and the fringe contrast map. And MATLAB is used to simulate the electronic shearography speckle pattern under different amount of shearing and generate a lot of valid images. The method for selecting shear is proposed through the combination of theoretical analysis and simulation. Tire deformation detection experiment achieves good results by using the method and verifies the effectiveness of the method. The research work on this article plays a practical guiding role on selection of shear in non-destructive detection system.

Gaussian radial basis function is usually applied as the kernel function of the kernel fisher discriminant analysis (KFD) in face recognition application. However, the parameter σ of the kernel function has a great impact on the classification. At present, the parameter is usually selected based on experience, and the process of KFD costs too much time for dealing with a large number of samples. To solve these problems, a method of face recognition is presented based on wavelet transform and improved KFD. It employs wavelet transform to compress the data of face image. And it applies PSO algorithm to automatically obtain the parameter to enhance the ability of classification when KFD is employed to complete feature extraction. Finally, support vector machine is used for classification. Numerical experimental results show that the method has a better operational efficiency and more accurate recognition rate than the traditional method of KFD.

A series of feature extraction algorithms based on locality preserving projection were proposed. Principal Component Analysis (PCA) algorithm must be firstly used for high-dimensional samples when these algorithms are applied in such as face recognition. Therefore，using unsupervised discriminant analysis algorithm as the theoretical basis，a direct unsupervised orthogonal locality preserving algorithm is proposed. Through the corresponding matrix decomposition according to the properties of the Laplace matrix, the projection matrix can be directly extracted from the original high-dimensional space without first using PCA algorithm processing and the proposed algorithm can solve the small sample size problem. To further improve the recognition performance, the orthogonal projection matrix obtained based on QR decomposition is given. Experimental results on face database and palmprint database demonstrate the effectiveness of the proposed method.

Fingerprint image is a special kind of gray image which consists with ridge and valley lines in black and white. The fingerprint image has different frequency component, low, medium and high frequency. The fingerprint image compression algorithm based on graded frequency is proposed. The low frequency sub-image, which contains the most energy, is encoded by lossless Differential Pulse Code Modulation (DPCM). The medium frequency sub-image, which contains less energy, is encoded by Embedded Zero-tree Wavelet (EZW). The high frequency sub-image, which contains the least energy, is encoded by Set Partitioning Embedded Block Coder (SPECK). The experimental result indicates, compared with the other image encoding method, the presented algorithm improves the compression ratio by about 21.4 percent and fidelity by about 6.25 percent in conditions of ensuring reconstruction quality.

The absorption spectrum, upconversion fluorescence spectrum and infrared absorption spectrum of Er3+-doped bismuth-germanate glass, which was prepared by conventional high-temperature melting-annealing method with the heavy metal oxide composition of Bi2O3-GeO2-PbO, are investigated, and the research focus is on the upconversion fluorescence mechanisms of Er3+ under the 975 nm and 800 nm laser excitation. The results show that the green and red emission centered around 529 nm, 552 nm and 667 nm, corresponding to the 2H11/2→4I15/2、4S3/2→4I15/2 和4F9/2→4I15/2 transitions of Er3+, respectively, are simultaneously observed under the 975 nm and 800 nm laser excitation. A two-photon upconversion process is assigned to the green and red emission. Compared to the 800 nm laser excitation, a more intense upconversion fluorescence can be obtained under the 975 nm laser excitation, and the green emission intensity is greater than that of the red emission, which indicates that the bismuth-germanate glass is a more promising glass host material applied to the green upconversion.

A blind robust image watermarking algorithm against row shifting was proposed, which used district points to design a revision method for resistance against row shifting to estimate row shifting number and turn row shifting into cropping. Firstly, at the embedding end, an original image was split into non-overlapping blocks. Then, a watermark was inserted by adjusting the numerical value of pixels from four columns in each block. Secondly, at the detection end, the revision method for resistance against row shifting was imposed on the watermarked image suffering from attacks. Then, a watermark was blindly extracted through pixel value comparison and majority judgment rule. The proposed algorithm has good invisibility and can achieve blind extraction. Moreover, the proposed algorithm has strong robustness against row shifting, since it adopted the revision method for resistance against row shifting. Experimental results also show that the proposed algorithm has strong robustness against common signal processing like Gaussian low-pass filtering, cropping, salt&pepper noise adding and Gaussian noise adding.

Aiming at the problem of bionic underwater vehicle’s research using fish swimming locomotion mechanism,from the point of view of image processing, fish’s soma moving model was established based on dynamic image sequences. First, attain fish’s contour by edge detecting, and present a method for soma extraction based on distance transform. Second, fit soma’s envelope and translational equation to attain parameter of slender body theory. Finally,establish fish’s soma moving model. The experimental results show that our model can describe fish swimming curve deformation under natural state more accurately and practically.

APEX Blind Image Restoration (BIR) is hardly real-time applied in image processing due to its slow speed, instability and the multi-input parameters process. Considering these limitations, according to the very important property in the image restoration process that there is a strong asymmetry between the dimensionality of the image and the Point Spread Function (PSF), the multi-region parameters estimate (MRPE) process is proposed, and the rationality of the MRPE process was proved by the Maximum-a-posteriori (MAP) estimate theory, and the feasibility of the multi-estimate process is illuminated by the experiments. Through the MRPE process method, the precision of the parameter estimation and usability are improved, and validity of the algorithm is validated by the experiments. This method is fast and robust, and can be applied for the low level noisy Gauss class blur image real-time image restoration.

Aiming at the problem of high error detection rate in complex background text location, a novel algorithm based on ant colony cluster algorithm is proposed for detecting and locating text regions in natural scene images. In the proposed method, firstly, statistical features of wavelet coefficients are used to represent text mode, and then ant colony cluster algorithm is selected to classify image pixels as text regions and background, thus all possible text regions are obtained. Secondly, Local Binary Pattern Histogram Fourier (LBP-HF) feature is applied to remove non-text areas which have the similar characteristics in wavelet domain. Experimental results demonstrate that verification procedure based on LBP-HF is effective, by which the error detection rate is reduced greatly for complex background text detection.

A new 2D-histogram called 2D-WLDH is proposed. At the same time, a new image thresholding method based on 2D-WLDH and maximum between-cluster variance is proposed. Moreover, the corresponding fast recursive algorithm is deduced. Regional division of the proposed 2D-WLDH can avoid the shortcomings of the traditional 2D histogram. The probability of the target and background of the image can be accurately estimated by calculating the small normalized Weber Local Descriptor (WLD) value. The experimental results show that, compared with the existing corresponding algorithm, the proposed fast recursive algorithm for maximum between-cluster variance threshold selection based on 2D-WLDH, achieves better segmentation quality, which obtains uniform regions, accurate borders and robust noise resistances. Furthermore, the running time of the proposed algorithm reduces by about 84.93%.