Title :
License plate localisation based on morphological operations
Author :
Zhai, Xiaojun ; Benssali, Faycal ; Ramalingam, Soodamani
Author_Institution :
Sch. of Eng. & Technol., Univ. of Hertfordshire, Hatfield, UK
Abstract :
Automatic Number Plate Recognition (ANPR) systems allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. This paper presents an improved method to locate car plates in an ANPR system. The proposed method is based on morphological open and close operations where different Structuring Elements (SE) are used to maximally eliminate non-plate region and enhance plate region. This method has been tested using a database of UK number plates and results achieved have shown significant improvements in terms of the detection rate compare to other existing plate localisation systems.
Keywords :
image motion analysis; image recognition; object detection; road vehicles; traffic engineering computing; ANPR systems; automatic number plate recognition systems; car plates; detection rate; enhance plate region; license plate localisation; morphological operations; moving vehicles; non-plate region; plate localisation systems; structuring elements; Classification algorithms; Feature extraction; Image color analysis; Image edge detection; Licenses; Morphological operations; Pixel; ANPR; morphological operation; number plate localisation;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-7814-9
DOI :
10.1109/ICARCV.2010.5707933