AUTOMATIC LICENSE PLATE LOCALISATION AND IDENTIFICATION VIA SIGNATURE ANALYSIS

• Published in: ICTACT journal on image and video processing Vol. 4; no. 3; pp. 754 - 761
• Main Authors: Angeline, Lorita, Pin Yoong, Hou, Lau, Hui Keng, Saad, Ismail, Kin Teo, Kenneth Tze
• Format: Journal Article
• Language: English
• Published: ICT Academy of Tamil Nadu 01.02.2014
• Subjects: 3D Image; Adaptive Searching; Automatic License Plate Recognition; Euclidean Distance Transform; Face Recognition; FRAV3D Database; Image Registration; Signature Analysis; Vehicle Localisation
• ISSN: 0976-9099; 0976-9102
• DOI: 10.21917/ijivp.2014.0109

A new algorithm for license plate localisation and identification is proposed on the basis of Signature analysis. Signature analysis has been used to locate license plate candidate and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents Signature Analysis and the improved conventional Connected Component Analysis (CCA) to design an automatic license plate localisation and identification. A procedure called Euclidean Distance Transform is added to the conventional CCA in order to tackle the multiple bounding boxes that occurred. The developed algorithm, SAICCA achieved 92% successful rate, with 8% failed localisation rate due to the restrictions such as insufficient light level, clarity and license plate perceptual information. The processing time for a license plate localisation and recognition is a crucial criterion that needs to be concerned. Therefore, this paper has utilised several approaches to decrease the processing time to an optimal value. The results obtained show that the proposed system is capable to be implemented in both ideal and non-ideal environments.