An automated vehicular license plate recognnition system for skewed images / Md. Yeasir Arafat

Md. Yeasir , Arafat (2018) An automated vehicular license plate recognnition system for skewed images / Md. Yeasir Arafat. Masters thesis, University of Malaya.

[img] Image (JPEG) (The Candidate's Agreement)
Restricted to Repository staff only

Download (650Kb)
    [img]
    Preview
    PDF (Thesis M.A)
    Download (5Mb) | Preview

      Abstract

      In recent years, automatic vehicular license plate recognition (AVLPR) framework has emerged as one of the most significant issues in intelligent transport systems (ITS) because of its magnificent contribution in real-life transportation applications. Restricted situations like stationary background, only one vehicle image, fixed illumination, no angular adjustment of the skewed images have been focused in most of the approaches. An innovative real time AVLPR technique has been proposed in this thesis for the skewed images where detection, segmentation and recognition of LP have been focused. A polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. The image gets reorganized in accordance with the image inclined slope by utilizing polar co-ordinate transformation procedure by proper revolving. This includes in the pixel mapping of new image to the old image for getting this Euclidean entity under the projective distortion. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighborhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested and the proposed method is able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs.

      Item Type: Thesis (Masters)
      Additional Information: Thesis (M.Eng.) - Faculty of Engineering, University of Malaya, 2018.
      Uncontrolled Keywords: License plates (LP); Intelligent transport systems (ITS); Character recognition; Connected component analysis (CCA); Skewed images
      Subjects: T Technology > TJ Mechanical engineering and machinery
      Divisions: UNSPECIFIED
      Depositing User: Mrs Rafidah Abu Othman
      Date Deposited: 08 Jul 2019 07:10
      Last Modified: 08 Jul 2019 07:10
      URI: http://studentsrepo.um.edu.my/id/eprint/9977

      Actions (For repository staff only : Login required)

      View Item