基于計(jì)算機(jī)視覺的三維測量技術(shù)畢業(yè)論文外文翻譯-閱讀頁
2024-11-26 04:14本頁面
【正文】 etric invariance。 wavelet transform。 the other is stereo matching problem. In this paper, neural work is used to approaching the mapping relation without camera calibration. Wavelet edge detection, searching nonsupervisor clustering and geometric invariance are applied to stereo matching. The multiscale and multiresolution attribute of wavelet is applied to image mosaic and data integration. In practice, the technology includes many methods and techniques, it can measure arbitrary size and shape object. However, the surfaces of some objects are smooth. Matching features are inconspicuous, so grating is projected on object. And the distorted stripes are created on object. They are regarded as matching features. For improving measurement precision, twocamera with converging opticalaxis is chosen. And the twocamera and the small selfmade projector constitute a flexible measuring head. A sketch of the 3D measurement principle based on stereo vision is shown in . 重慶理工大學(xué)畢業(yè)設(shè)計(jì) 外文翻譯 11 3 Establishment of the Mapping Relation Between Image Point and Special Point Actually, obtaining 3D information of object from a pair of two images is by mapping relation between image point and special point, but until now no approach can pletely describe the nonlinear mapping relation since there are many plex nonlinear influencing factors including radial distortion and lateral distortion of camera. However, neural work can simulate human vision to establish plex mapping by simple nonlinear processing cells, so this paper regards the middle process from image point to special point as a black box. And BP work with a middle layer of six neural cells is used to set up the mapping relation between image point and special point. Point A ( , )llxy in left image and a point ( , )rrxy in right image are input into the BP work, a special point ( , , )xyz is output. In other words, the structure of BP work is 463. Using neural work, the choosing of training samples is important The training samples not only lie in the measurable range, but also show measurement range of measurement system. While twocamera is used to grab object, the object and the part of object only in 重慶理工大學(xué)畢業(yè)設(shè)計(jì) 外文翻譯 12 jointing viewing field can be able to be grabbed. So 3D information of object from a pair of stereo images, lens focus, measurement precision, once measuring area and the distance between object and baseline of twocamera control 3D measurement range of the system are obtained. In this paper, the structure and function of the two cameras that are posed symmetrically are identical, and the image area is 22xyTT? , just as . The lens focus is f。t accord with the practical situation of stripe edge points. Before curves are fitted, not only is the number of groups given, but also which group a point belongs to is known, and the number of groups is equal to the number of stripe edges. Therefore, a searching nonsupervisor clustering 重慶理工大學(xué)畢業(yè)設(shè)計(jì) 外文翻譯 14 algorithm is proposed in this paper. If D is an aggregate of points, n is number of points in D, and if D is divided into M groups, dividing approach is shown as follows. 1) If iX is attribute vector, {1, 2, 3, }ni N n?? ???? is known as initial group ? , that is iX???,the number M of groups is equal to n。 3) On the basis of under hood, the distance min( , )kld ?? between two groups is puted for all groups. If kX ??, 39。 39。( ) ( )TX X X X X X? ? ? ? (T stands for transpose), that is min( , )kld ?? = min{ 39。 4) i? and j? are merged into i?, that is i j i? ? ??, so the total of groups decrease 1。 39。( , )k k kandl l l by perspective transform. The image straight lines have also corresponding straightline equation parameters. And the parameters are shown with superscript (for example 139。39。39。39。39。 the distance between the surface and the two cameras is 500mm. A 150150 mm 2 curve surface is measured with the technology, measurement results are shown in Tab. 1, and measurement steps are given as follows: 1) Establish the mapping relation between image points and special points。 3) Process image, remove background, and reduce noise, just as , 3b。 5) Search corresponding points, and mosaic imag
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