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Representation of Shape Based on Laser Stripe Projection and Modelling with Bezier Approximation Networks

机译:基于激光条纹投影的形状表示和Bezier逼近网络建模

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摘要

An automatic technique for the representation of the object shape is presented. The main aim of this technique is the extraction of the topography and the shape of articles by networks. Based on laser stripe projection, the topography is obtained automatically using Bezier approximation networks. Using the topographic dimension, a two-dimensional Bezier approximation network is able to calculate the shape of an object. The topography is detected by scanning the object by the laser stripe. The scanning produces a set of images of the laser stripe, which are processed by Bezier approximation networks to determine the object dimensions. The Bezier approximation network calculates the dimensions according to the behaviour of the laser stripe. Based on these dimensional data, the Bezier network produces an object model. This model is a replica of the object shape. The idea behind the Bezier approximation networks is to obtain the shape of an object without any measurements being carried out on the optical setup. Thus, the performance of the experimental setup and the accuracy of the results are improved. This is due to the fact that errors of measurement are not passed on to the computational model. The accuracy is assessed by taking the root mean square of the error and data produced by Bezier approximation networks and the data obtained by a contact method. This technique is tested with real objects and the experimental results are presented and assessed.
机译:提出了一种用于对象形状表示的自动技术。该技术的主要目的是通过网络提取地形和物品的形状。基于激光条纹投影,使用Bezier近似网络自动获得地形。使用地形尺寸,二维贝塞尔近似网络能够计算物体的形状。通过激光条纹扫描物体来检测形貌。扫描产生一组激光条纹图像,这些图像由Bezier近似网络处理以确定物体尺寸。贝塞尔曲线近似网络根据激光条纹的行为来计算尺寸。基于这些维度数据,贝塞尔网络将生成一个对象模型。此模型是对象形状的副本。 Bezier近似网络背后的思想是获得物体的形状,而无需在光学装置上进行任何测量。因此,实验装置的性能和结果的准确性得以提高。这是由于测量误差没有传递到计算模型这一事实。通过采用误差的均方根以及由Bezier逼近网络产生的数据以及通过接触法获得的数据来评估准确性。该技术已通过实际物体进行了测试,并给出并评估了实验结果。

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