Automatic License Plate Localization Using Intrinsic Rules Saliency
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2011, Vol 0, Issue 1
Abstract
This paper addresses an intrinsic rule-based license plate localization (LPL) algorithm. It first selects candidate regions, and then filters negative regions with statistical constraints. Key contribution is assigning image inferred weights to the rules leading to adaptability in selecting saliency feature, which then overrules other features and the collective measure, decides the estimation. Saliency of rules is inherent to the frame under consideration hence all inevitable negative effects present in the frame are nullified, incorporating great deal of flexibility and more generalization. Situations considered for simulation, to claim that the algorithm is better generalized are, variations in illumination, skewness, aspect ratio and hence the LP font size, vehicle size, pose, partial occlusion of vehicles and presence of multiple plates. Proposed method allows parallel computation of rules, hence suitable for real time application. The mixed data set has 697 images of almost all varieties. We achieve a Miss Rate (MR) = 4% and False Detection Rate (FDR) = 5.95% in average. Also we have implemented skew correction of the above detected LPs necessary for efficient character detection.
Authors and Affiliations
Chirag N. Paunwala, , Dr. Suprava Patnaik
Keywords
Related Articles
- EP ID EP140110
- DOI -
- Views 105
- Downloads 0
Secure and Efficient Routing Mechanism in Mobile Ad-Hoc Networks
Securing crucial information is always considered as one of the complex, critical, and a time-consuming task. This research investigates a significant threat to the security of a network, i.e., selective forwarding attac...
Comparison of Digital Signature Algorithm and Authentication Schemes for H.264 Compressed Video
In this paper we present the advantages of the elliptic curve cryptography for the implementations of the electronic signature algorithms “elliptic curve digital signature algorithm, ECDSA”, compared with “the digital si...
Estimating Null Values in Database Using CBR and Supervised Learning Classification
Database and database systems have been used widely in almost, all life activities. Sometimes missed data items are discovered as missed or null values in the database tables. The presented paper proposes a design for a...
Tuning of Customer Relationship Management (CRM) via Customer Experience Management (CEM) using Sentiment Analysis on Aspects Level
This study proposes a framework that combines a supervised machine learning and a semantic orientation approach to tune Customer Relationship Management (CRM) via Customer Experience Management (CEM). The framework extra...
Detection of Cardiac Disease using Data Mining Classification Techniques
Cardiac Disease (CD) is one of the major causes of death. An important task is to identify the Cardiac disease very minutely and precisely. Generally medical diagnostic errors are dangerous and costly. Worldwide they are...