This article presents an algorithm to avoid camera overexposure or underexposure by calculating and analyzing the camera response function. First, the range of intensity value and time is set to ensure that the intensity value of each image pixel is within the measurement range when the camera's exposure time is within the time range. Then, the reference image which has the maximum number of pixel intensity values within the intensity value range is selected. Third, the camera response function will be calculated based on the variation of the reference point intensity value with the exposure time. Finally, the whole exposure times will be recovered based on the computed response function, and used in the process of structured light measurement. The experimental results verify the performance and feasibility of the proposed method.
The focus variation microscopy is widely used and researched in both industrial and academic field. But the 3D construction quality of surface topography is affected by the noise, the double peak value, and the discontinuous surface, and so on. A simulation method for focus variation is proposed based on the physical model of optical imaging and the Point Spread Model(PSF). At first, the linear relationship between the blur factor σ of Gaussian function and the defocus distance δ is deduced which is called point spread parameter λ, then, considering the positive correlation between blur factorσ and blur degree, the difference between the real defocused image and the calculated image by Gaussian convolution operation to real captured focused image is shown. It is used to the objective to computed the accurate value σ and the spread parameter λ. At last, the difference between focus measure valued of real image sequence and simulation image sequence is used to verify the method. The simulation method is a judgement basis for focus measurement, the single peak of focus curve, and the identification of high-frequency noise.
Increasing requirements on the complexity and accuracy of dimensional metrology demand the application of aerospace turbine blade, cutting tools, and so on. The multi-scale data of holistic geometrical is needed. In order to obtain all meaningful details of the surface at various required scales, a novel trans-scale optical measurement method mixing macro and micro measurement technology is proposed. The optical scanning system is composed of a variable-focus structured light sensor fitted with zoom lens camera and a focus variation microscopy sensor. The structured light sensor is used to acquire the form of the object. The focus variation microscopy sensor is used to acquire the waviness or roughness of the object. The macro structured light sensor can flexibly zoom in or out to measure a 3D object profile in sections according to the approximate surface profile and the view of the micro measurement system. It originally connects the macro and micro scale at view, resolution, precision. The different scale measurement data are registered and fusion with multi-dimensional images which includes 2D image, 2.5D range image, and 3D point cloud image. Experimental measurement results show that macro holistic geometry profile and micro surface texture can be acquired with the developed method in a single frame system.
To measure the shape of object with high-speed and avoid the disturbance of the vibration is remaining challenges faced by structured-light projection method. This paper proposes a high-speed optical metrology by coding three cosine patterns into three channels of RGB model to form the pattern. When the color image is obtained by camera, it will be transformed to HSI color model (hue, saturation and intensity). The hue component is regarded as the phase information to retrieve the 3D shape of object with single image, while the saturation and intensity are applied to avoiding phase errors caused by height steps or spatially isolated surfaces. This method can be used to measure object with non-monochromatic surfaces after the color compensated. Experimental results verify the feasibility of the developed method.
Single line scanning is the main method in traditional 3D hand-held laser scanning, however its reconstruction speed is very slow and cumulative error is very large. Therefore, we propose a method to reconstruct the 3D profile by parallel multi-line 3D hand-held laser scanning. Firstly, we process the two images that contain multi-line laser stripes shot by the binocular cameras, and then the laser stripe centers will be extracted accurately. Then we use the approach of stereo vision principle, polar constraint and laser plane constraint to match the laser stripes of the left image and the right image correctly and reconstruct them quickly. Our experimental results prove the feasibility of this method, which improves the scanning speed and increases the scanning area greatly.
This paper presents a novel registration method by encoding feature point identification and spatial location to make the registration of 3D measurement easy. A new proposed decoding algorithm based on polar coordinate segmentation is first used for identification feature point, the feature points are then measured and constructed. The overlapped 3D measurement feature points within two views are used to unify coordinate system, so the feature points of each view are achieved for global spatial location. The object is finally measured with any view which only contains at least three feature points. The unconstrained 3D registration is acquired with the feature points matching between single measurement view and global spatial points. Our experiments show that the proposed method is convenient and effective, and greatly enhances the flexibility of 3D measurement applications.
A new technique for coded targets recognition in optical 3D-measurement application is proposed in this paper. Traditionally, point cloud registration is based on homologous features, such as the curvature, which is time-consuming and not reliable. For this, we paste some coded targets onto the surface of the object to be measured to improve the optimum target location and accurate correspondence among multi-source images. Circular coded targets are used, and an algorithm to automatically detecting them is proposed. This algorithm extracts targets with intensive bimodal histogram features from complex background, and filters noise according to their size, shape and intensity. In addition, the coded targets’ identification is conducted out by their ring codes. We affine them around the circle inversely, set foreground and background respectively as 1 and 0 to constitute a binary number, and finally shift one bit every time to calculate a decimal one of the binary number to determine a minimum decimal number as its code. In this 3Dmeasurement application, we build a mutual relationship between different viewpoints containing three or more coded targets with different codes. Experiments show that it is of efficiency to obtain global surface data of an object to be measured and is robust to the projection angles and noise.
Accurate and robust phase unwrapping is an important procedure for three dimensional (3D) profilometry measurement. The mask cut phase-unwrapping algorithm merges the characteristics of Goldstein's branch cut and reliability-guided path-following algorithms, so that it has higher accuracy and stability. However, it cannot handle discontinuous phase regions because it completely relies on the phase quality map to guide the placement of mask cuts, thereby easily causing phase error propagation. To overcome these drawbacks, we propose a new phase-unwrapping method that merges the residue check principle and a Laplace phase derivative variance quality map that we developed. First, the entire phase was divided into several isolated regions in accordance with the quality map. Then, each pixel of the absolute phase marker line was taken as the starting point to unwrap the discontinuous phase regions based on reliability guidance. In addition, a new list-trimming algorithm was employed to guarantee a speedy phase-unwrapping procedure. The entire phase unwrapping and accurate 3D measurement of discontinuous objects was successfully completed. The simulated and experimental data both demonstrate the validity of the proposed phase-unwrapping algorithm.
Structured light system using a digital micro-mirror device (DMD) projector is increasingly used for a 3-D shape measurement because of its digital nature. When the DMD projector is used in phase measuring profilometer (PMP), the precision of profile measurement will increase with the precision of phase-shift increasing. But the non-sinusoidal nature of the projected fringe patterns causes significant phase measurement error and consequent shape measurement error. In the reality, we find that the non-sinusoidal effect is never caused by only one factor. A real measurement shows that it is a combination of influences by all effects, e.g., the object independent irradiance function, the nonlinear gamma curve of the projector, the spatio-temporal characteristic of DMD, etc. In view of the above factors, a comprehensive compensation method is proposed to compensate these factors for the 3D measurement. If the compensation is well accomplished, the measurement error can be reduced average 6 times. The experiment is carried out to demonstrate the validity of this technique.
In this paper a multivariable robust controller design approach of the ACLS is accomplished by using robust
loop-shaping techniques. In order to avoid the inefficient way of choosing the weight functions by trial-and-error
method, the structured genetic algorithm (SGA) approach is introduced, which is capable of simultaneously searching
the orders and coefficients of the pre- and post-compensator for weight matrices. According to this approach, engineers
can achieve an ideal loop-shape which lies in an appropriate region relating to the desired performance specifications.
The effectiveness of this approach is illustrated by the longitudinal equations of a carrier-based aircraft's motion design