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Automatic Recognition for Losing of Train Bogie Center Plate Screw Based on Multiple-Fuzzy Relation Tree

机译:基于多模糊关系树的列车转向架中心板螺丝丢失自动识别

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Automatic recognition of losing of bogie center plate screw (BCPS) on digit images is a hard problem that due to the vast differences and impreciseness associated with the poor sampling environment and moving photographing. This paper presents a multiple-fuzzy relation tree to solve this problem. Single sample is preprocessed by the method such as finite-radius Hough transformation, constraint-rectangle calculator and the gray average of local domain to obtain elements construct the fuzzy sets. Multiple-fuzzy relation tree was designed based on the rules based on fuzzy sets. Demonstrated by application, the multiple-fuzzy relation tree has an advantage with the recognition of complex pattern, strong correlation and low contrast images. The recognition accuracy is achievable up to 90%.
机译:由于不良的采样环境和移动摄影带来的巨大差异和不精确性,在数字图像上自动识别转向架中心板螺钉(BCPS)的丢失是一个难题。本文提出了一种多模糊关系树来解决这个问题。通过有限半径霍夫变换,约束矩形计算器和局部域灰度平均等方法对单个样本进行预处理,得到构成模糊集的元素。基于基于模糊集的规则,设计了多模糊关系树。通过应用演示,多模糊关系树具有识别复杂图案,强相关性和低对比度图像的优点。识别精度最高可达90%。

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