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LPR (License Plate Recognition) is a foundation component of modern transportation management systems. It uses a set of computer image-processing technologies to identify vehicle by its license plate. Character recognition is the core of LPR, which is essentially a multi-classification problem. The challenge is how to recognize every character of the license plate accurately and rapidly in case of...
We present a license plate detector using a fusion of Maximally Stable Extremal Regions (MSER) and SIFT-based unigram classifier trained with Core Vector Machine (CVM). First, MSER is used to obtain a set of regions. Highly unlikely regions are removed with a simplistic heuristic-based filter. Finally, remaining regions with sufficient positively classified SIFT keypoint are retained as likely license...
Find a car in large park is a challenge for intelligent parking lot management system. In this paper, an intelligent car-searching approach for large parking lot is presented. In the new approach, some cameras are set up in each road. Vision information of the car, including car color and license plate are recognized and saved in database. Considering that no license plate recognition system can 100%...
This paper presents a two-stage method to detect license plates in real world images. To do license plate detection (LPD), an initial set of possible license plate character regions are first obtained by the first stage classifier and then passed to the second stage classifier to reject non-character regions. 36 Adaboost classifiers (each trained with one alpha-numerical character, i.e. A..Z, 0..9)...
A method of number-plate characters recognition using AdaBoost algorithm, which based on template matching is presented in order to improve recognition rate and reduce recognition time. The method is divided into two stages. In the first stage, classifier is trained by template matching which is improved through AdaBoost classification, at the same time, classification rules are found. Number-plate...
High accuracy and fast recognition speed are two requirements for real-time and automatic license plate recognition system. In this paper, we propose a hierarchically combined classifier based on an inductive learning based method and an SVM-based classification. This approach employs the inductive learning based method to roughly divide all classes into smaller groups. Then the SVM method is used...
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