Because of high accuracy and wide range, the advanced optoelectronic imaging deflection system has become the important device of the Bridge Structural Health Monitoring System (BSHMS), and has been applied to several bridges. However, the recognition accuracy of the optoelectronic imaging deflection system has greatly descended for fog and sunshine in practice. By analyzing the principle of image-based deflection measurement, a conclusion was drawn that small error in light source target in image recognition caused larger error in deflection because of amplification of optical measurement system. A novel method based on projection and differential is proposed for recognition of light source target. Compared with conventional method (its Mean-Square Error (MSE) is 16.534 08 and 23.018 13), the proposed approach (its MSE is 1.632 231 and 2.182 247) is more accurate and accords with practice. Experiment results verify the effectiveness of the designed method and theoretical discussions.

To improve the measurement accuracy of the binocular vision system, the binocular vision system error model is established. Meanwhile, the influence of camera calibration accuracy and the lens parameters and structural parameters of vision system on system accuracy are analyzed. And the rationality of the theoretical analysis is verified by experiment. The experiment results show that, when placing calibration targets at the different depths relative to the camera of the entire field of view, the system accuracy can be improved effectively by increasing the number of calibration image. The system error can be reduced by increasing the baseline distance in the premise of effective field of view. And the system has higher measurement accuracy while the angle values between the baseline and the optic axial range from 55o to 70o.

When the surface color of the same material and different gloss objects is measured, in order to remove the color measurement impact caused by the surface gloss, the diffuse illumination, the viewing angle of 8-degree illumination and specular component included illumination viewing conditions are mostly chosen. Ideally, because of the homogenization effect of integrating sphere on illumination light, the measurement result is not affected by the surface gloss. However, in the real instrument design, owing to the constraints in measuring structural design, the color measurement results of the test samples with the same spectral reflectance and different surface gloss are different. This paper theoretically analyzes the cause of the deviation in the illumination viewing condition of the diffuse illumination, the viewing angle of 8-degree illumination and specular component included illumination, when measuring the material surface color of different gloss. This paper also designs a measurement structure which can simultaneously measure the data of color and gloss, presents a correction model which can modify the SCI measured data according to the surface gloss data of the test sample, and then designs relevant experiments to test and verify. The experimental results show that, using the correction model for modifying the measurement structure, the measurement error can be significantly reduced.

To establish a method of comparing record CCD camera’s performance in ultrafast optic diagnostic systems (e.g. streak cameras, frame cameras based on gated micro channel plate intensifier, etc.), the CCD camera’s main performance parameters were compared and discussed. It is the analyzing result that CCD camera’s lower detectable limit and dynamic range both are the most important aspects of these systems. Two rules that can ensure one comparing different CCD cameras’ performance without installing them onto a virtual system were introduced. First, the pixel group associated with the minimal resolvable element of the system should be treated as a unit so that the CCD cameras with different pixel number and different pixel size can be compared fairly. Second, the minimal detectable optic power and the optic dynamic range are both chosen to be the appropriate parameters for evaluating the performance among CCD cameras with different digital levels and output fluctuations. A demonstration system for evaluating different CCD cameras offline was constituted where a scientific grade CCD camera and an EMCCD camera were tested. Compared with the scientific grade CCD camera, the EMCCD camera’s minimal detectable optic power is lower and its dynamic range is wider. The method was successfully applied in the constitution of the ultrafast optic diagnostic system for Zpinch.

As is well known, gaseous chlorine dioxide holds great prospect for room disinfection, but the technology of on-line concentration monitoring is immature, which hinders its widely use to a great extent. Based on absorption photometry principle, using LED as a light source, the differential absorption type measuring unit with simplified single wavelength and double light paths was designed. This paper realized the concentration sensor of gaseous chlorine dioxide with a detection range of 0~9 mg/L. Various measures were taken to avoid the photochemical decomposition of gaseous chlorine dioxide in the detection process to improve the stability of the sensor. Additionally, the experiment platform was designed to calibrate the sensor. The result shows that the design can meet the demand of on-line concentration monitoring for room disinfection using gaseous chlorine dioxide, with the accuracy of better than 2% of full scale.

A background suppression method based on B-spline surface fitting was proposed to solve the problem of the accuracy of Mura detection, which is often caused by the uneven brightness and complex background when employing machine vision on Mura detection of TFT-LCD. Under the constraint of least square criterion, bicubic B-spline surface fitting algorithm was deployed to fit the uneven brightness background and a fairing item was added to adjust fitting precision. In order to increase the performance of the proposed algorithm and decrease the calculation time, divided fitting method was used on original image and the bicubic B-spline function was analyzed into one-dimensional functions for efficiently solving. Furthermore, pathological problems caused by solving of the two-dimensional functions could be avoided simultaneously. The effect on the Mura defect segmentation caused by uneven brightness background was eliminated by subtracting the fitted background from the original image. The experimental results show that the proposed method can suppress the uneven brightness background efficiently and Mura defect can be segmented accurately after background suppression.

For the technical difficulties of defect detection on high-speed wire surface, the segmentation technology of wire defects under complex illumination is researched. As the gradient histogram has multi-peak, a peak selection standard is described and then a piecewise self-adaptive fuzzy threshold method is provided based on the fuzzy threshold with double humps. Using this method, the wire can be segmented from the complex background. In order to extract the defect edges ahead, a contraposition traversal method is provided. The final test results shows that the methods provided can deal with the continuous gray problem caused by uneven illumination and extract the defect accurately, and thereby lay a foundation for the further study on the vision recognition of wire defects.

Aimed at the detection difficult problem of feather quill crease, the idea of non-linear manifold is introduced into crease target recognition. A feather quill crease recognition method based on locality preserving projection and manifold kernel function is proposed for feature extraction. Firstly, covariance matrices are computed as the crease descriptors of feather quill, and an affine invariance metric which is adopted to make the space meet the requirement of Riemannian manifold is used to measure the distance between the two samples. Secondly, the neighbors of a selected point can be determined by the proposed manifold kernel function to make choice of the nearest neighboring points in line with the hypothesis of data distribution with non-linear manifold. The kernel matrix is defined based on the manifold distance and category labels. Finally, the locality preserving projections algorithm is used to reduce the dimensionality of the feather quill images. The simulated experiment results suggest that the proposed algorithm is robust to the variation of illumination and residual noises image segmentation, and achieves better performance compared with many popular recognition algorithms．

Pedestrian detection is a major difficulty in object recognition. Features used for pedestrian detection are high in dimension. We use principal component analysis to reduce the dimension of features, and make the detection algorithm run faster. It overcomes the influence of the high dimensional features which reduce the real-time of pedestrian detection. The information content of single feature is limited. To make use of multi-source information feature, we fusion some low-level features (color、gradient、histogram) and multi-level oriented edge energy feature based on the linear discriminant analysis of linear weighted fusion strategy. Features can be calculated fast by integral image technique. The robustness and real-time performance of pedestrian detection system have been strengthened. Histogram intersection kernel support vector machine have the advantage of fast classification and high accuracy in object recognition. It can be used for further enhancing the system real-time performance. The experiments show that the proposed algorithm has faster detection speed and higher precision than the classical algorithm HOG+SVM.

The Fixed Pattern Noise (FPN) of the infrared focal plane array severely limits the system performance, and the non-uniformity correction algorithm is a key technique of thermal imaging system. The scene-based non-uniformity correction algorithm does not require a shutter to block the field of view, but utilizes the scene information of image sequences to calculate the infrared focal plane array non-uniformity parameters. This paper introduces an improved neural network non-uniformity correction algorithm, which speeds up the convergence rate of the conventional neural network algorithm. The improved algorithm employs the edge detection method to overcome the ghosting artifacts generated by the conventional algorithm. The algorithm has run on a small low power consumption DSP hardware platform with TMS320DM643 as the kernel processor and can do the correction in a simple way with satisfactory results, so the algorithm introduced in this paper is proved to be reasonable and effective.

The research on infrared radiance characterization of the satellite is of great significance in satellite infrared detection and recognition and the satellite infrared stealth design. In this paper, firstly, the radiant heat flux of satellite was calculated. Secondly, each surface temperature changed with orbit cycle was calculated. On this basis, the self-emitted infrared radiation and its reflecting infrared radiation from the environment of the various satellite surfaces were calculated, thus a mathematical model to calculate the satellite infrared radiant periodic characteristics was established. Finally, taking a hexahedron satellite in an orbit for instance, the radiant luminance of MIR and FIR in atmospheric window and its change with time on its body's six different surfaces during the period on the orbit were calculated. Results can provide the reference for satellite infrared detection and infrared stealth design.

A long-wave infrared continuous 6× zoom optical system with 640×512 uncooled infrared thermal detector is designed and described. It contains 6 lenses and works at 8~12μm wavelength with the F# of 1~1.1. Based on the theory of zoom optical lenses design, a mechanical compensation structure is determined and the initial structure parameters are calculated. Moreover, the optical system parameters and zoom curves are designed and optimized. The image quality assessment shows that system zooms continuously and smoothly in all 20~120 mm focus lengthens range. The Modulation Transfer Function (MTF) values at 30 lp/mm are all above 0.45 and the spot diagrams’ RMS radius are all less than 6.3 μm which is much smaller than the detector pixel size 17 μm in all focus lengths range. The experiment proves that this zoom system has the merits of high resolution, high zoom ratio, big aperture, big field range, and has steady image plane and zooms smoothly with compact structures and low cost.

An infrared small target detection method is proposed based on sparse representation assisted by ridge regression. The proposed method constructs over-complete dictionary with target samples and background samples which are produced by two-dimensional Gaussian model and normal random matrix respectively. Infrared small target detection consists of two stages. In the first stage, the construction errors of detect samples are calculated fast using ridge regression. In the second stage, candidate samples are selected adaptively by ridge regression reconstruction errors, and infrared small targets are detected with the reconstruction errors of the candidate samples selected which are computed with sparse representation. The experimental results on several infrared images show that the proposed method is faster and more robust than the existing methods.

Reflected light is partly polarized, and current research shows that thermal infrared emission is also partly polarized. Using Kirchhoff's law and Fresnel formulas, we made preliminary theoretical analysis and some simulation on thermal infrared emission polarization. Under the experimental environment of low temperature and taking shelter measures, we carried out verification experiment of thermal infrared emission polarization and obtained some experimental data of thermal infrared emission polarization of aluminum plates with different surface states and solar panel. Experimental results show that thermal infrared emission is partly polarized, and have consistent variation with the simulation results. Thermal infrared emission polarization is affected by surface roughness and material of the target. With the increase of viewing angle, the degree of polarization increases.