Application of machine learning to classify surface marker of screw

Chuan-Yu Chang, Hung-Chang Shie
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Abstract

In recent years, many character recognition methods had proposed for recognizing handwritten or computer characters. However, there is few paper discusses marker recognition on screw. General speaking, screw images suffered from the influences of splotch and reflection. How to classify the marker of the screw is still a challenging problem. Therefore, we applied the machine learning to recognize the markers on surface of the screw. Experimental results shown that the proposed method achieves reasonable classification accuracy.
机器学习在螺旋表面标记物分类中的应用
近年来,针对手写或计算机字符的识别,提出了许多字符识别方法。然而,关于螺旋上的标记识别的研究却很少。一般来说,螺旋图像受到色斑和反射的影响。如何对螺钉的标记进行分类仍然是一个具有挑战性的问题。因此,我们使用机器学习来识别螺钉表面的标记。实验结果表明,该方法达到了合理的分类精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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