Title :
Adaptive local thresholding based number plate detection
Author :
Oksuz, Cosku ; Gullu, M. Kemal
Author_Institution :
Elektron. ve Haberlesme Teknolojisi Programi, Kastamonu Univ., Kastamonu, Turkey
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.
Keywords :
brightness; feature extraction; image segmentation; lighting; object detection; object recognition; adaptive local thresholding based number plate detection; automatic number plate recognition approach; character features; character regions; complex background; connected component analysis; dark regions; distance condition; horizontal projection; inclination condition; licence plate area detection; pixel luminance values; variable illumination; Character recognition; Computer vision; Licenses; Optimized production technology; TV; Transforms; Plate extraction; local thresholding; projections;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130113