Study On Several Key Questions In Visual Inspection

With the advantages of fast measuring speed, non-contact, high accuracy, easy operationand automatic measuring, etc, the stereo vision inspection technique has played a significantrole in many areas. We discussed some key problems about the stereo vision inspectionpractically and theoretically. The major content is as follows:1、In order to overcome camera calibration needs user to give additional information ofcalibration pattern, or fully-automatic identification algorithm of calibration points can’tdetect calibration points in the presence of significant occlusions, uneven illumination,observations under extremely acute angles and lens distortion, an improved checker patternbased on fiducial markers is designed, and its correspondingly fully-automatic identificationof calibration points is proposed. New camera calibration pattern replace black and whitesquares of traditional checker pattern with fiducial markers, so fully-automatic identificationalgorithm can locate markers. Using the priori knowledge that markers are arrangedsequentially into calibration pattern in accordance with markers’ ID from small to large, themissed calibration points can be located. In order to improve the estimate of initial position ofmissed points in image, radial distortion is estimated, so identification algorithm overcomethe impact of lens distortion. In order to improve location accuracy of calibration points,subpixel-accurate saddle points’ finder is used. In order to validate the potential points, twofiltering criteria is performed, finally valid calibration points is obtained. The detectionalgorithm is efficient and free of parameters.2、A lot of traditional camera calibrations compute the pin-hole and lens distortionmodels at the same time, so two models are coupled, computed calibration results are validonly for training data, and their calibration errors increase for new data. In order to overcomethe coupling of two models, a calibration which calibrate two models separately is proposed.The algorithm uses geometric invariants of calibration template, which are cross-rationinvariability and the projection of straight line in the space to the camera is a line, to computeundistorted coordinates of distorted calibration point, and then compute two models linearly.The proposed algorithm is stable and has high calibration accuracy.3、Vision measurement system is usually subjected to the interference of impulse noise.In order to remove impulse noise from the obtained digital images and also preserve image edge features, impulse noise filter based on gray consistency is proposed. The proposed filteris composed of an impulse noise detector and an adaptive switching median filter. Becauseimpulse noise is some mixture between the fixed-valued impulse noise and the random-valuedimpulse noise, the detector first utilizes the noise image histogram to identify the fixed-valuedimpulse noise, then utilizes direction templates to detect whether detected point meet thecriterion of gray consistency with pixels in any direction, and classifies any possiblerandom-valued impulsive noise pixels. Subsequently, adaptive switching median filter usesbinary decision map to determine whether the filter is implemented and determine thedimensions of filtering window, and replaces the detected noise pixels with the median pixelof all noise-free pixels in filtering window. In order to obtain the optimum performance, thefiltering scheme that adaptively determines the number of iterations is proposed. Theproposed filter is capable of filtering impulse noise and has the relatively fast processing time.4、Analysis the deficiencies of original Canny edge detection algorithm, the improvedCanny edge detection algorithm is proposed. First, the algorithm use small-scall Gaussianfunction to smooth image, improve location accuracy of edge detection algorithm. Second, ituse Otsu dual-threshold algorithm to calculate the dual-threshold of gradient amplitudeadaptively, use Otsu single threshold algorithm to calculate the threshold of grayscale, whichlimits the high threshold of gradient magnitude, more accurately finds the edge, excludes themeaningless edge. The improved canny edge detection algorithm avoids set parametersartificially, meet the needs of industrial inspection, has good anti-making performance, edgelocation accuracy and real-time.5、Analysis the nature of error edge, propose the criterions to exclude error edges,improve the speed and accuracy of edge matching. Use the corner detector based on thechord-to-point distance accumulation technique to detect the festure points of remainingedges. Use a few constraints to limit the search of candidate matching feature points, then useedge descriptor to find right matching point. Edge descriptor is composed of grayscale mean,grayscale standard deviation and edge direction histogram. Edge descriptor has excellentmatching performance, and is invariant to occlusion, translation, rotation and linearillumination. The edges including matching feature points are matched, use edge to constrainthe range, and use epipolar constraint to achieve fast matching of edge points.6、Analylysis the requirements of accuracy shipbuilding for hull section visual inspectionsystem, that is to obtain the three-dimensional data of the edge of hull section, so thehardware design of the hull section visual inspection system is proposed. Hardware iscomposed of mechanical servo system, vision sensor, image acquisition system and computer. This paper gives the selection of hardware, and focuses on analysis of the structural design ofvision sensor. At the same time, it gives the implementation method of hull section scanning,including measuring method based on moving coordinate, hull section scanning mode basedon location trigger, trigger mode of camera and image acquisition card. High-performancehardware guarantees the measurement accuracy and speed of the hull section visual inspectionsystem. High-precision detection results guarantee the establishment of marginless dockingand compensation system about hull section.