Road Sign Detection from Edge Orientation Histograms

This paper presents a system for road sign detection based on edge orientation histograms. Edge orientation histograms are reliable, scale and contrast invariant features that can be extracted efficiently using integral images. A learning method is introduced that selects features based on the implicit transmission function of the designer´s template to the object´s appearance in the image. The system is able to detect 85% of the objects on from 12 pixels width and 95% for objects on from 24 pixels width at a low false alarm rate.