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Research Of License Plate Location Algorithm Based On Principal Component Analysis And Fisher Linear Discriminant

Posted on:2008-08-09Degree:MasterType:Thesis
Country:ChinaCandidate:M YangFull Text:PDF
GTID:2178360215979733Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
With the developing of information technology and intelligence technology, the informatization and intelligentizing of traffic management become more and more important. License Plate Recognition system (LPR) is the core of Intelligent Traffic System (ITS). It is very important in modern traffic management systems.In recent years, using the computer to deal with and analyses image has already obtained progress at full speed. The study on the critical techniques for LPR has already become an important research field of scientific circles.In this paper we discussed the three parts of License Plate Recognition Systems: image pre-process, license plate location and character segmentation, and made a deep research about some important and key technology.A hybrid license plate segmentation scheme is presented in this paper. The mainly three stages of this approach are designed to deal with images taken under various real world conditions. Generally, the images of complex background, license plate skew and different plate size are used in our experiment.In this paper, a coarse to fine algorithm to locate license plates in images and video frames with complex background is proposed. First, the method based on Component Connect (CC) is used to locate the possible license plate regions in the coarse detection. Second, the method based on texture analysis is applied in the fine detection. Finally, a FLD is adopted as classifier, the feature vectors is decreased the dimensionality by PCA to make the FLD efficient. The average accuracy of location is 95.3% from the images with different angles and different lighting conditions.Based on the experimental results, it proves that this proposed method can relatively locate license plate and segment characters and the performance of the system is promising. It shows that combined feature extractions and location techniques can improve the ability of system.
Keywords/Search Tags:Image Processing, Principal Component Analysis, Fisher Linear Discriminant, Feature Extraction
PDF Full Text Request
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