Vision based Traffic Panel Text Information and Sign Retrieval

Abstract

We propose a novel system for the automatic detection and recognition of text in traffic sign boards. 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 interpreted using optical character recognition (OCR).