Adaptive local thresholding based number plate detection

Abstract

In this paper, an automatic number plate recognition approach with low computational load has been proposed to detect licence plate area using character features. In the preprocessing step, unlike classical Sauvola method the output is weighted according to the pixel luminance values, and therefore dark regions are eliminated from the detection. After preprocessing step, regions that cannot show a character property are eliminated using connected component analysis, and then character regions are detected utilizing horizontal projection. Experimental results show that proposed method works faster and gives better detection performance in complex background, variable illumination, distance and inclination conditions.