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中文摘要：
通过工业计算机断层成像图像边缘拟合,可获得矢量化的曲线,进而获得工件的计算机辅助设计图纸,实现基于工业断层成像的机械零部件逆向设计。在用两组细胞神经网络对图像进行分割的基础上,进行边缘跟踪和曲线的多维拟合。通过横截圆和轴线的拟合,实现对圆柱形目标的拟合。轴线拟合时,将各层圆心坐标分别投影到xz平面和yz平面进行最小二乘拟合,以降低计算复杂度。对发动机切片图像进行实验,根据拟合得到的参数得出了圆柱形目标的计算机辅助设计图,其拟合均方误差小于0.3像素2。对不规则目标,讨论了基于最小二乘法的分段三次曲线拟合方法在边缘曲线拟合中的应用;对发动机切片图像目标区域进行实验的拟合均方误差均小于0.6像素2。实验结果和误差分析证明,文中的拟合方法是有效的,实现了基于工业断层成像的逆向设计所必需的位图矢量化。
英文摘要：
Through the edge fitting of Industrial Computed Tomography（ICT） images,vector-based curves,and the Computer Aided Design（CAD） drawings of work-pieces could be achieved to realize the reverse design of the inspected work-piece.Based on the image segment with two groups of Cellular Neural Networks（CNN）,the edge trace and multidimensional curves fitting were discussed.To fit the cylindrical object,fitting methods of cross circle and the axis line were presented.Through projecting the center coordinates of all floors＇ circle onto the XZ,YZ plane and fitting respectively by the least square,the computation complexity of the axis line＇s fitting was reduced.According to fitting parameters,the CAD drawing of the engine slice images＇ cylindrical object was obtained,and the mean square error was less than 0.3px2.For the irregular objects,the piecewise cubic curve-fitting based on the least square was presented.To fit the engine slice images＇ target area,the mean square error was all less than 0.6px2.Experimental results and the error analysis validated the fitting methods.And the bitmap＇s vector required in the reverse design based on ICT was realized.
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同项目期刊论文
The construction of 2D rotationally invariant wavelets and their application in image edge detection
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