Traffic sign shape classification evaluation. Part II. FFT applied to the signature of blobs

P. Gil-Jiménez, S. Lafuente-Arroyo, H. Gómez-Moreno, F. López-Ferreras, S. Maldonado-Bascón
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引用次数: 61

Abstract

In this paper we have developed a new algorithm of artificial vision oriented to traffic sign shape classification. The classification method basically consists of a series of comparison between the FFT of the signature of a blob and the FFT of the signatures of the reference shapes used in traffic signs. The two major steps of the process are: the segmentation according to the color and the identification of the geometry of the candidate blob using its signature. The most important advances are its robustness against rotation and deformation due to camera projections.
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交通标志造型分类评价。第二部分。FFT应用于blobs的签名
本文提出了一种新的面向交通标志形状分类的人工视觉算法。该分类方法基本上是将blob特征的FFT与交通标志中使用的参考形状特征的FFT进行一系列的比较。该过程的两个主要步骤是:根据颜色进行分割和使用候选blob的特征识别其几何形状。最重要的进步是它抗旋转和变形由于相机投影的鲁棒性。
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