Recognition of Number Plate for Vehicle Identification using Dynamic Image Processing Techniques in Intelligent Transportation System
In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various
environments. The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm.
The proposed algorithm employs an interpolated Probability Distribution Value (PDV) in order to control a sudden change
in image brightness. Probability distribution value can be calculated using Cumulative Distribution Function (CDF) and
Probability Density Function (PDF) of the captured image, whose values are achieved by brightness distribution of the
captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it
provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a
binary image, which fuses narrow breaks, eliminates small holes, and fills gaps in the contour by using morphology
operations. Then license plate region is detected based on aspect ratio. The images have been captured by using a video
camera. The captured images have included several license plates on multilane roads. Simulation has been executed using
Open CV and MATLAB. The results show that the extraction success rate is more improved than the conventional
algorithms. Potential applications includes vehicle parking facilities and campus security system for permitting authorized
vehicles into the premises.
Index Terms - Probability Distribution Value, Car License Plate Extraction, Contrast Enhancement, Cumulative
Distribution Function, Genetic Algorithm, Intelligent Transportation System