License plate recognition (LPR) technology has great importance for the development of Intelligent
Transportation Systems by automatically identifying the vehicles using image processing
and pattern recognition techniques. Conventional LPR systems consist of license plate
detection (LPD), character segmentation (CS) and character recognition (CR) steps. Successful
detection of license plate and character locations have vital role for proper LPR. Most LPD
and CS techniques in the literature assume fixed distance and orientation from the vehicle to
the imaging system. Hence, application areas of LPR systems using these techniques are
limited to stationary platforms. However, installation of LPR systems on mobile platforms is
required in many applications and algorithms that are invariant to distance, orientation, and
illumination should be developed for this purpose. In this thesis work, a LPD algorithm that
is based on multi-scale vertical edge density feature, and a character segmentation algorithm
based on local thresholding and connected component analysis operations are proposed. Performance
of the proposed algorithm is measured using ground truth positions of the license
plate and characters. Algorithm parameters are optimized using recall and precision curves.
Proposed techniques for each step give satisfying results for different license plate datasets
and algorithm complexity is proper for real-time implementation if optimized.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613723/index.pdf |
| Date | 01 October 2011 |
| Creators | Karali, Ali Onur |
| Contributors | Ulusoy, Ilkay |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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