Adaptive traffic road sign panels text extraction

In this paper we present an approach to the detection and extraction of text in road sign panels. Text strings, indicators and signs extraction is efficiently performed so OCR algorithms can recognize different characters that may be present on the traffic plane. In a first step, basic color segmentation and shape classification is done for the purpose of detecting possible rectangular planes. Every detected plane is extracted from the original image and then reoriented. Chrominance and luminance histogram analysis and adaptive segmentation is carried out, and connected components labeling and position clustering is finally done for the arrangement of the different characters on the panel. Special emphasis has been placed on the adaptive segmentation. Experimental results have showed that following steps strongly depends on correct separation between the background and foreground objects of the panel. Moreover, OCR systems are highly sensitive to noise, and we have put special attention into it in order that the OCR system could be able to recognize characters properly.