Study on Algorithms of Graphic Element Recognition for Precise Vectorization of Industrial Computed Tomographic Image

F. Liu, B. He, B. Bi
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引用次数: 2

Abstract

Circle, line and circular arc are the common basic graphic elements in industrial computed tomography (ICT) image. The algorithm of recognizing such elements is the key to industrial CT image precise vectorization. An industrial CT image vectorization system has been studied, including different recognition methods for these elements. Firstly, based on facet model, the sub-pixel edge of an industrial CT image is extracted. Then, the circles are recognized by an improved algorithm based on probability of existence map, while the lines are recognized with the set intersection algorithm of fitting a straight line, and the circular arcs are recognized by the combination of the perpendicular bisector tracing algorithm and least squares function. Finally, the graphic element parameters are measured according to recognition results, and the drawing exchange file (DXF) is produced and transmitted into the computer aided design (CAD) system to be edited and consummated. The experimental results show that these methods are capable of recognizing graphic elements in industrial CT image with an excellent accuracy, besides, the absolute errors of circles are less than 0.1 mm, and the relative errors are less than 0.5%. It can satisfy the industrial CT vectorization requirements of higher precision, rapid speed and non-contact.
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面向工业计算机层析图像精确矢量化的图形元素识别算法研究
圆、线和圆弧是工业计算机断层扫描(ICT)图像中常见的基本图形元素。这些元素的识别算法是实现工业CT图像精确矢量化的关键。研究了一个工业CT图像矢量化系统,包括对这些元素的不同识别方法。首先,基于facet模型提取工业CT图像的亚像素边缘;然后,采用改进的基于存在映射概率的圆识别算法,采用拟合直线的集合交算法识别直线,采用垂直平分线跟踪算法与最小二乘函数相结合的方法识别圆弧。最后根据识别结果测量图形元素参数,生成图形交换文件(DXF),并传输到计算机辅助设计(CAD)系统中进行编辑和完善。实验结果表明,该方法能较好地识别工业CT图像中的图形元素,且圆的绝对误差小于0.1 mm,相对误差小于0.5%。能够满足高精度、快速、无接触的工业CT矢量化要求。
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