提出了一种新的识别户外不同交通标志形状的算法。为了减少数字噪声的影响和分离提取独立的交通标志形状，基于颜色分割输出的外边缘可通过离散曲线演变进行简化和分解。正切空间中弧线的相似程度决定离散曲线演变的程度。形状的识别是通过模板匹配来实现的，待识别形状与模板之间的最小几何差异决定形状的类别。实验结果表明本算法是平移、旋转和尺度恒定的，能够在复杂的交通场景中进行可靠的形状识别。

A novel approach for detecting and recognising various traffic sign shapes in outdoor environments is proposed.In order to reduce the influence of digital noise, separate and extract the shape of each individual traffic sign, the external boundaries of traffic signs segmented based on color information are simplified and decomposed through discrete curve evolution.The evolution level is determined by the arc similarity measure in tangent space.The recognition of a candidate shape is achieved through matching against templates.The minimum geometric difference between a candidate shape and templates is utilized to determine the classification of the candidate shape.The experimental results justify that the proposed algorithm is translation, rotation, and scaling invariant, and gives reliable shape recognition in complex traffic scenes.