An automated vehicular license plate recognnition system for skewed images / Md. Yeasir Arafat - Md. Yeasir , Arafat (2018)
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.