26-05-2012, 05:49 PM
An Automatic & Robust Vehicle License Plate
Recognition System
An Automatic & Robust Vehicle.pdf (Size: 190.96 KB / Downloads: 242)
Abstract
An automatic and robust vehicle license plate
recognition system has been developed. The proposed method
uses scan line evaluation and averaging method to localize the
number plate followed by a border removal mechanism
combined with character mending and approximation of
character height to extract the number plate characters. Finally,
a template matching approach is used to recognize the
characters. A Graphical User Interface has been created and the
algorithm is experimented successfully on a variety of real
images, both single as well as double line plates. The sample
results obtained on testing with various images are also detailed.
INTRODUCTION
The onerousness involved in number plate localization and
recognition is very well known in the field of Digital Image
Processing and the encumbrance increases as more and more
factors are to be taken into consideration. Each vehicle has a
unique identification number which is portrayed in its license
plate. Number plate recognition system exploits this
uniqueness to make it suitable to put in use with a variety of
applications such as border crossing monitoring, toll
management, parking management etc. With the
implementation of such an efficient security system we can put
a curb on the increasing crime rate.
LITERATURE REVIEW
A. Plate localization
Plate localization is done to remove the unwanted
background details, and thereby focusing on to the essential
details in the image.
To detect the car plate, a method by applying a top-hat
filter to the whole image followed by a multiscale region
search has been described [4]. Another approach has been
proposed to detect the vertical edges, to extract the license
plate using sobel operators [3]. A technique using edge
detection and hough transforms, to detect the vertical and
horizontal edges, by making use of the rectangular shape of
the license plate has been presented [6]. Sorin developed an
approach to analyse the input image, looking for areas with
high contrast gradients at the given scale of about 15 pixels
followed by histogram stretching [7].
B. Character extraction
Character extraction is done by segmenting the character
portions from the localized number plate. Noise contents that
may also be present along with these number plate characters,
makes the job a tedious one.
CONCLUSION AND FUTURE WORK
The paper explicates on license plate recognition
emphasizing a scan line evaluation method to localize the
license plate and a border removal mechanism combined .