| In the application of the projection fringe method,a large amount of post-processing work is often required.Because the field of view of the camera is not exactly equal to the area of the object to be measured,and measurement of unnecessary information is also included in the measurement process,the amount of data to be processed and the source of noise are increased.Therefore,these noises need to be removed during the post-processing process..The existing image edge recognition algorithm can overcome the above problem well,and automatically and intelligently recognize the effective region,ie,the edge of the object to be detected,so that the effective region of the image can be segmented and the region can be processed only.Therefore,the combination of image edge recognition algorithm and projection fringe method can effectively reduce the amount of data to be processed to improve the post-processing efficiency,and can effectively reduce the noise introduced by unnecessary information,significantly improve the signal-to-noise ratio of image data and the reconstruction of topography.quality.In this paper,by introducing the non-contact optical measurement method,the realization steps of the projected fringe method and the error control scheme are introduced step by step,and then several kinds of image edge recognition operators and their processing effects are further introduced.Based on this,the method proposed in this paper is introduced: by applying the image edge recognition operator to image segmentation,the post-processing steps of the projection fringe method can be simplified.That is,the image segmentation technology can be used to automatically filter out-of-edge background noise instead of tedious.The manual filtering,and can get higher signal-to-noise ratio image data.At the end of the article,3DMAX and Matlab software were used to simulate the experiment.Compared with the manual filtering results,the advantages of this method can be clearly seen. |
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