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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >A new active contour modeling method for processing-path extraction of flexible material
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A new active contour modeling method for processing-path extraction of flexible material

机译:柔性材料加工路径提取的主动轮廓建模新方法

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Due to properties of flexible material, uneven thickness, cutting speed, rapid changing feed direction and other factors in path processing of flexible material, the edge of processing path image become fuzzy, causing difficulty of improving edge detection precision. In this paper, after analyzing characteristics path contour of flexible material, taking gray-level integration of target area as a regional energy, and adding it to traditional Snake model which is widely used in edge extracting of complex geometric shapes, combining image edge with region information to build a new Region Snake (R-S) model, therefore by certain transformation, the description of total energy of contour can be replaced by force acting that moving on the contour. In new R-S model, matrix expression of discrete force balance equation of contour is obtained by discretization of finite difference method, then derivative terms are introduced and to get the calculation formula of processing path contour curve through Euler iteration method; finally by judging local extremum of covariance matrix of curve to realize corner detection. Three patterns with different shape characteristics were used to test the R-S model, Experimental results show that, the target contour curves of three patterns are completely extracted, the mean square errors of extracted curves are less than 0.35%, the detection rates of corners are greater than 90%, these prove that the R-S model proposed for flexible materials processing path contour extraction has high calculation accuracy and good stability, the method of corner detection is very suitable for flexible material processing path contour. (C) 2016 Elsevier GmbH. All rights reserved.
机译:由于柔性材料的性质,厚度不均匀,切割速度,进给方向的快速变化以及柔性材料的路径处理中的其他因素,处理路径图像的边缘变得模糊,从而导致难以提高边缘检测精度。本文在分析柔性材料的特征路径轮廓之后,将目标区域的灰度积分作为区域能量,并将其添加到传统的Snake模型中,该模型广泛用于复杂几何形状的边缘提取,将图像边缘与区域结合起来。信息以建立新的Region Snake(RS)模型,因此,通过一定的变换,可以用作用在轮廓上的力代替轮廓总能量的描述。在新的R-S模型中,通过有限差分离散化得到轮廓离散力平衡方程的矩阵表达式,然后引入导数项,并通过欧拉迭代法得到加工路径轮廓曲线的计算公式。最后通过判断曲线协方差矩阵的局部极值来实现拐角检测。用三种形状特征不同的图案对RS模型进行测试,实验结果表明,三种图案的目标轮廓曲线被完全提取,提取曲线的均方误差小于0.35%,拐角检测率更高。超过90%,证明了提出的用于柔性材料加工路径轮廓提取的RS模型具有较高的计算精度和稳定性,转角检测方法非常适合柔性材料加工路径轮廓的提取。 (C)2016 Elsevier GmbH。版权所有。

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