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.