首页|改进Steger算法流程的激光条纹中心提取

改进Steger算法流程的激光条纹中心提取

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在三维测量与重建的过程中,准确地提取激光条纹的中心位置至关重要.然而,由于Steger算法运算量庞大,难以满足工业领域对实时性的迫切需求.为克服Steger算法运算量大、提取效率低的难题,首先,采用波峰波谷阈值分割的方法对预处理过的图像进行阈值分割,以降低图像的复杂性;其次,通过设置最小矩形面积和最小长宽比查寻感兴趣区域,提取感兴趣区域以减少算法的冗余计算;最后,对感兴趣区域用改进后的Steger算法进行中心提取.经过实验数据分析,所提算法保留了传统Steger算法的精度和有效提高了Steger算法的运算速度,这为实时进行三维重建提供了有力支持.
Improved Laser Fringe Center Extraction for Steger Algorithm Process
In the process of 3D measurement and reconstruction,it is important to accurately extract the center position of the laser stripe.However,due to the huge amount of computing of Steger's algorithm,it is difficult to meet the urgent needs of real-time in the industrial field.In order to overcome the problem of large computation and low extraction efficiency of Steger's algorithm,this paper improves it to accelerate the extraction of the center position of laser stripes.Firstly,the threshold segmentation method of peak and trough threshold segmentation is used to reduce the complexity of the preprocessed image.Then,by setting the minimum rectangular area and minimum aspect ratio,the region of interest is searched to reduce the re-dundant calculation of the algorithm.Finally,the region of interest is centrally extracted using the improved Steger algorithm.After experimental data analysis,the proposed algorithm retains the accuracy of the tradi-tional Steger algorithm and effectively improves the operation speed of the Steger algorithm,which provides strong support for real-time three-dimensional reconstruction.

Stegercenter extractionthreshold splittingarea of interest

邓仕超、何新凯

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桂林电子科技大学广西制造系统与先进制造技术重点实验室,桂林 541004

Steger 中心提取 阈值分割 感兴趣区域

2024

组合机床与自动化加工技术
大连组合机床研究所 中国机械工程学会生产工程分会

组合机床与自动化加工技术

CSTPCD北大核心
影响因子:0.671
ISSN:1001-2265
年,卷(期):2024.(10)