Road sign recognition

A method for recognizing road signs in street scene images is proposed.; We first developed a fast region growing segmentation method, combined with a 1NN smoothing filter, to work on color and produce robust segmentation results even when the image is noisy. An effective color distance measurement is developed to work with the segmentation.; We then designed a hierarchical feature representation scheme, which organizes model features in a tree structure. The tree nodes are components that form the basic parts of a model, and the tree leaves are primitive physical features that can be mapped directly to basic features in segmented image. A matching error model was defined to work with the feature representation scheme.; To deal with the complexity in object detection, we designed an anchor feature and its detection scheme for the use of alignment detection. Alignment transformations are further verified by a unified matching scheme, which integrates feature ordering and performance tactics into one process.; We used a modified Hausdorff distance as the final verification method in matching a candidate to the model. An efficient algorithm in calculating the distance using Voronoi diagram based on edge map as point set is developed. (Abstract shortened by UMI.)...