Pin Cao

Dark-field microscopic image stitching method for surface defects evaluation of large fine optics

One of the challenges in surface defects evaluation of large fine optics is to detect defects of microns on surfaces of tens or hundreds of millimeters. Sub-aperture scanning and stitching is considered to be a practical and efficient method. But since there are usually few defects on the large aperture fine optics, resulting in no defects or only one run-through line feature in many sub-aperture images, traditional stitching methods encounter with mismatch problem. In this paper, a feature-based multi-cycle image stitching algorithm is proposed to solve the problem. The overlapping areas of sub-apertures are categorized based on the features they contain. Different types of overlapping areas are then stitched in different cycles with different methods. The stitching trace is changed to follow the one that determined by the features. The whole stitching procedure is a region-growing like process. Sub-aperture blocks grow bigger after each cycle and finally the full aperture image is obtained. Comparison experiment shows that the proposed method is very suitable to stitch sub-apertures that very few feature information exists in the overlapping areas and can stitch the dark-field microscopic sub-aperture images very well.

Automated discrimination between digs and dust particles on optical surfaces with dark-field scattering microscopy

To make the surface defects evaluation system (SDES) of fine flat optics more effective and reliable, the point-like defects on the surface are divided into two categories: digs and dust particles. Since only the digs are the real damages that should be sent for further investigation, the false signals associated with dust particles should be distinguished and removed. Dark-field scattering microscopy and pattern recognition methodology are combined to classify digs and dust particles. The SDES is employed for dark-field image acquisition of optical samples. Gray scale, texture, and morphology analyses are then conducted on each image to extract raw feature data, which are compressed with the principal component analysis. Based on the compressed feature data, the support vector machine is used to construct the classification model. The success discrimination rates are 96.56% for the training set and 93.90% for the prediction set. The classification results are presented to show the potential of this method to be used for practical digs and dust particles discrimination on the actual optical samples.

Sparse microdefect evaluation system for large fine optical surfaces based on dark-field microscopic scattering imaging

It is considered challenging to evaluate the sparse microdefects of large optical surfaces because the microdefects are usually of microns while the test samples are of hundreds of millimeters. Most of the existing methods encounter problems such as uncertainty and inefficiency in eyeballing, inconsequence between laser source and international standard, limitation of detecting area, qualitative but not quantitative nor standard measurement of defects, etc. In this paper, a dark-field microscopic scattering imaging system for microdefects evaluation is introduced. The principle of the proposed surface microdefect evaluation system will be presented and the experiment results on evaluating numerous of test samples will be given.

Research on digital calibration method for optical surface defect dimension

A digital calibration method for defect dimension of the optical surface is put forward to get the correspondence between the actual scale of defect on optical surface and the number of pixels of the defect image captured by CCD. Standard scratches, with their width ranging from 0.5μm to 40μm, are fabricated by electron beam exposure and reactive ion beam etching on two kinds of standard calibration board, quartz calibration board with and without chromium film. Calibration experiments are accomplished in five different microscope magnifications. Threshold segmentation, morphological operation and feature extraction are carried out in the images of calibration board to obtain the width of standard scratches in pixels. Interpret the theoretic trend of the calibration function as well as the linear range of it, and fit the calibration function based on the experimental results. According to the analysis and comparing of the calibration results in different microscope magnifications, error source and the factors limiting the resolving accuracy of the calibration system are analyzed. Ultimately, a standardization process including fabrication of the standard scratch, establishment of the standard calibration library for different microscope magnifications and the rapid calibration of actual detect is established. The calibration of the defects on the optical element in the size of 450mm× 450mm is successfully realized.

Digital calibration method for defects evaluation of large fine optical surfaces

The digital calibration method, which is employed in the Surface Defects Evaluation System (SDES) for the defects evaluation of large fine optical surfaces, is presented in this paper. A criterion board, which comes from special design and careful fabrication, is employed to relate the dimensions of the defects and those of their images. The calibration procedure, including collecting of calibration images, digital image processing and calibration function fitting, is described in detail in this paper. Calibration experiments on scratch width and dig diameter were carried out at three different microscope magnification conditions. Experiment results show that following the proposed digital calibration method, micron-sized defects distributed sparsely on a large-aperture fine optical surface can be evaluated with micron accuracy and high efficiency.

Study on distortion correction for image mosaic of surface defects

It is hard to quantitate the micron-scale defects on large aperture (102mm×102mm) optical components by the conventional optical testing methods. This paper proposes a super-smooth surface defects measurement and evaluation system, achieved by using microscopic dark-field scattering imaging device, two-dimensional sub-image scanning mechanism and multi-cycle image mosaic algorithm. The defects detecting system, with a lateral resolution of 0.5μm, applies a large field of view design (largest FOV: 15mm×15mm). In order to test the largest element (430mm×430mm), however, over 1000 sub-pictures are captured. It takes more than 30 minutes to process these sub-pictures by multi-cycle image mosaic algorithm. This paper also presents a distortion correction method to revise the image mosaic mismatch caused by the optical distortion in the defects testing system on the platform of MATLAB. A binary optical grid plate (BOE) is fabricated as standard board to evaluate distortion. The proposed method applies image division multi-steps to build a look-up matrix of distortion parameters. According to the look-up matrix, all pixels on a sub-image are repositioned from the distortion Cartesian coordinates to the ideal Cartesian coordinates. Finally, feasibility of the distortion correction method is demonstrated by comparing the mosaic results of defect images before and after this process. The full field view distortion is reduced from more than 4% to less than 0.1%. After distortion correction, subimages can be directly mosaicked without using multi-cycle image mosaic algorithm, which improves test efficiency significantly. The method mentioned in this paper may also apply to other optical testing systems for image mosaic.

Application of image entropy evaluation function for the leveling of large aperture components in auto defects detecting

In large aperture component’s dark-field scattering defects imaging system, the component’s size is large and part with a wedge. When the component is in the completely level position, the surface defects image can be clearly acquired by a high magnification microscope. Otherwise, fuzzy defects image would be gained because of defocusing which makes digital identification can’t be able to be done. For the problem of leveling large aperture, wedge component, this paper proposes a method that using image information entropy as focusing evaluation function for leveling large aperture components. Firstly, in three different points of component surface acquiring multi-images by the same continuous steps. Then calculating the images’ entropy and fitting a curve to it. Based on minimum image information entropy value criterion, the focal plane can be found and each point’s defocusingamount of the fist acquisition position can be gained. Relay on the relation model of acquisition points, adjust points and defocusingamount that has been built, each adjust point’s adjustment can be got. The component’s level position can be achieved by adjusting the adjust points. In the experiment that using a high magnification (of 16) microscope scans over the whole surface of the component with the size of 430mm×430mm. The image microscope is always in the depth of focus which shows that the leveling precision has achieved 20μm. Until now, this method has been successfully used in large aperture component’s dark-field scattering defects imaging system.

Numerical simulation research and applications on scattering imaging of surface defects on optical components

The principle of microscopic scattering dark-field imaging is adopted in surface defects evaluation system (SDES) for large fine optics. However, since defects are of micron or submicron scale, scattering imaging cannot be described simply by geometrical imaging. In this paper, the simulation model of the electromagnetic field in defect scattering imaging is established on the basis of Finite-Difference Time-Domain (FDTD) method to study the scattering imaging properties of rectangular and triangular defects with different sizes by simulation. The criterion board with scribed lines and dots on it is used to carry out experiments scattering imaging and obtain grayscale value distributions of scattering dark-field images of scribed lines. The experiment results are in good agreement with the simulation results. Based on the above analysis, defect width extraction width is preliminary discussed. Findings in this paper could provide theoretical references for defect calibration in optical fabrication and inspection.

Algorithms and applications of aberration correction and American standard-based digital evaluation in surface defects evaluating system

The inspection of surface defects is one of significant sections of optical surface quality evaluation. Based on microscopic scattering dark-field imaging, sub-aperture scanning and stitching, the Surface Defects Evaluating System (SDES) can acquire full-aperture image of defects on optical elements surface and then extract geometric size and position information of defects with image processing such as feature recognization. However, optical distortion existing in the SDES badly affects the inspection precision of surface defects. In this paper, a distortion correction algorithm based on standard lattice pattern is proposed. Feature extraction, polynomial fitting and bilinear interpolation techniques in combination with adjacent sub-aperture stitching are employed to correct the optical distortion of the SDES automatically in high accuracy. Subsequently, in order to digitally evaluate surface defects with American standard by using American military standards MIL-PRF-13830B to judge the surface defects information obtained from the SDES, an American standard-based digital evaluation algorithm is proposed, which mainly includes a judgment method of surface defects concentration. The judgment method establishes weight region for each defect and adopts the method of overlap of weight region to calculate defects concentration. This algorithm takes full advantage of convenience of matrix operations and has merits of low complexity and fast in running, which makes itself suitable very well for highefficiency inspection of surface defects. Finally, various experiments are conducted and the correctness of these algorithms are verified. At present, these algorithms have been used in SDES.

Research on auto-centering device in surface defects evaluation system of large spherical optics

For the Spherical Surface Defects Evaluation System (SSDES), lens centering is essential to obtain the precise scanning trace and defect features without mismatch. Based on a combination of auto-collimating microscopy and Computer-Aided Alignment (CAA), an auto-centering system that can measure the deviation of large spherical center with respect to a reference rotation axis rapidly and accurately is established in this paper. The auto-centering system allows the closedloop feedback control of spherical center according to the different images of the crosshair reticle on CCD. Image entropy algorithm is employed to evaluate image clarity determined by the auto-focus experiment of 50μm step-length. Subsequently, an improved algorithm that can search the crosshair center automatically is proposed to make the trajectory of crosshair images and the position of rotation axis more reliable based on original circle fitting algorithm by the least square method (LSM). The comparison results indicates to show the high accuracy and efficiency of the proposed fitting method with LSM.