We propose a novel system for the automatic detec-tion and recognition of text in traffic signs. Scene structure is
used to define search regions within the image, in which traffic
sign candidates are then found. Maximally stable extremal regions
(MSERs) and hue, saturation, and value color thresholding are
used to locate a large number of candidates, which are then
reduced by applying constraints based on temporal and structural
information. A recognition stage interprets the text contained
within detected candidate regions. Individual text characters are
detected as MSERs and are grouped into lines, before being in-terpreted using optical character recognition (OCR). Recognition
accuracy is vastly improved through the temporal fusion of text
results across consecutive frames. The method is comparatively
evaluated and achieves an overallFmeasureof 0.87.
Maximally stable extremal region (MSER), scene
structure, text detection, traffic text sign recognition.