Automatic system recognition of Lebanese license plates

TitreAutomatic system recognition of Lebanese license plates
Type de publicationCommunications avec actes
Année de publication2010
Titre de la Conférence/colloqueIEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA
Pagination1399 - 1405
Dates du congrès, colloque2010
Langueeng
Auteur(s)Akoum, A. Hussain, Daya B. et Chauvet P.
Complément de titreIEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA
Ville, PaysLiverpool
Mots-clésArabic line, automatic system recognition, character extraction, character identification, French line, fusion of basic algorithm, image classification, image processing, image processing technology, Image segmentation, k-mean classification, labeling classification, Lebanese license plates, object detection, object recognition, system recognition, vehicle identification, vehicles
Résumé

License Plate Recognition is an image-processing technology that is used to identify vehicles by their Lebanese license plates. A license plate reader works by extracting the characters from an image. This technology is used for many applications such as toll booths, parking decks, border control, and law enforcement. As a solution to the problem of monitoring the tremendous number of vehicles for law enforcement and security, we use two methods of classifying the Lebanese plate in several areas: Labeling and K-Mean. Then, we have to extract from the plate the two classifications, which are the French line and the Arabic line. We separate each character from each line using the vertical profile method. Then we would recognize the characters by the algorithm of the K-PPV with a rate of recognition of the characters: The Arabic writing is of 82% and the Western writing is of 91 %. Finally we use a vote method between the two writings to increase the rate of recognition up to 93%.

Notes

Date du colloque : 09/2010

URLhttp://okina.univ-angers.fr/publications/ua1547
DOI10.1109/BICTA.2010.5645286