This document describes a method for license plate detection and recognition. It involves preprocessing the image, using morphological operations to isolate the license plate region, and then locating the plate. The method uses operations like rotation, filtering, thresholding, closing and opening to prepare the image and isolate the plate. The results show the algorithm works well on some images but not on others, due to factors like plate angle, brightness, and size variations.

1. Zafer Genç

2.  Goals
 Description of Method
 Conclusion and results

3. 1. Using ‘Morphological Image Processing’ and
other image processing methods to leave
plate alone in the image
2. Finding the location points of the plate in
that image

4.  It consists of four steps :
Morphological Image Processing
Image Preprocessing
Finding Plate Location
Drawing Lines

5. This step makes the image prepared for
morphological image processing.
Things are done in this step :
1. Reading image
2. Rotating image 180˚ degree
3. Converting RGB image to YIQ
4. Taking the Gray level of YIQ image (‘Y’
component)
5. Passing the gray image through the
unsharp filter

6. 6. Adding result of usharp filter process to the
gray image
7. Converting gray image to the binary image
with giving a threshold
8. Passing the binary image through LoG
filter to use later
9. Clearing the noise of the binary image with
median filter
10. Making black of some parts that the plate
can never exist , from up and down of the
image
11. Clearing noise of the result image with
median filter

8.  The reason of image 180 ˚ degree is making
the plate location more suitable to be found.
Down parts of images are always less
complex than the other parts of images.

9.  There are two reasons of obtaining gray level from the YIQ .
One is the YIQ gray level has less noise than gray level of
RGB. Other reason is the contrast of the YIQ gray level is
better than the RGB. The plate is black letters on white
background ,so it is good to increase the contrast.

10.  Another thing can increase contrast is sharpening the image
with ‘unsharp filter’. After passing image through the
unsharp filter , result is added to the image , therefore it can
be more sharpen , and the contrast would be high.

11.  Converting gray image to the binary image with
giving a threshold :

12.  Places that an plate can not exist in upper and lower parts of the
result binary image is painted black . Therefore, the area that is
morphological image processing would be apply is made smaller .
The smaller area is better for the morphological image processing,
because the areas that would be eliminated later are decreased.

13.  Erosion and dilation make important change on height and
width of parts . They are not used . Only closing and opening
are used.
 Things are done in this step :
1. Closing operation with rectangle structural element ( size=
[10 60] )
2. Opening operation with rectangle structural element (
size= [5 30] ) to remove small objects.
3. Filling the white areas from left to right and from right to
left until finding a black pixel
4. again closing operation with structural element of rectangle
(size [5,30])
5. opening operation with structural element of rectangle
(size [10,60])
6. Result is passed through a median filter to get rid of noise.

14. 7. Closing operation is done again with a
rectangle (size [5,30]) .
8. z=(s3-edge); (edge is the result of LoG
filter operation in preprocessing step)
9. reverse the final image . (z1=1-z );

16.  First Closing operation with rectangle
structural element ( size= [10 60] )

17.  Opening operation with rectangle structural
element ( size= [5 30] )

18.  Filling the white areas from left to right and from right to
left until finding a black pixel. If black pixel comes, then it is
done in that line and jump to the next line. The purpose of
this operation is increase the black areas and leaving less
white areas ,therefore finding the plate would be easier ,
because the plate would be the one of the white areas. Also,
the plate is between black pixels ,so it is not effected from
this operation .

19.  Second closing – opening operations :

20.  z=(s3-edge) operation and taking the
reverse

21.  Because many images are experimented with this algorithm , it is
necessary to define margin values when drawing lines

22.  The algorithm works well with some images , but it
does not work with some other images. Reason of this
is the angle of plates, brightness of some images,
different size of plates in images and the using same
structural elements for all images.