Traffic sign shape classification based on correlation techniques
Traffic sign shape classification based on correlation techniques
复制标题
基于相关技术的交通标志形状分类
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
F. J. Acevedo
中科院分区：
文献类型：
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作者：
A. Vázquez;S. Lafuente;P. Siegmann;S. Maldonado;F. J. Acevedo
在本文中，我们提出了一种基于相关性的交通标志形状分类匹配方法。我们的目的是提供一个强大而可靠的框架，可用于驾驶员辅助系统等众多应用程序。形状分类是尺度、平移和旋转不变的。该过程涉及从每个区域获取基本特征（例如边缘、脊、角），并将其与存储的已知图案模板进行比较。该算法非常灵活，易于针对许多不同的形状进行重新配置，我们获得的结果显示了成功率。
In this paper we present a correlation-based matching method for traffic sign shape classification. Our purpose is to offer a robust and reliable framework which can be used in numerous applications like driver assistance systems. The shape classification is scale, translation and rotation invariant. The process involves obtaining essential features (e.g. edges, ridges, corners) from each area, and comparing it to the stored templates of known patterns. The algorithm is very flexible, easy to reconfigure for many different shapes and the results we obtained show the success rate.