Abstract In recent years, the necessity of personal working in traffic control is increasing because the numbers of vehicles in traffic is increasing. To deal with this problem, computer based automatic control systems are being developed. One of these systems is automatic vehicle license plate recognition system. In this work, the automatic vehicle license plate recognition system based on artificial neural networks is presented. In this system, 259 vehicle pictures were used. These vehicle pictures were taken from the CCD camera and then the license plate region dimensioned by 220×50 pixels is determined from this picture by using image processing algorithms. The characters including letters and numbers placing in the license plate were located and determined by using Canny edge detection operator and the blob coloring method. The blob coloring method was applied to the ROI for separation of the characters. In the last phase of this work, the character features were extracted by using average absolute deviation formula. The digitized characters were then classified by using feed forward back propagated multi layered perceptron neural networks. The correct classification rates were given in last section.
[1]
Ergun Erçelebi,et al.
Automatic Vehicle Identification by Plate Recognition
,
2007
.
[2]
T. Tan,et al.
Iris Recognition Based on Multichannel Gabor Filtering
,
2002
.
[3]
Tim Morris,et al.
Computer Vision and Image Processing: 4th International Conference, CVIP 2019, Jaipur, India, September 27–29, 2019, Revised Selected Papers, Part I
,
2020,
CVIP.
[4]
Dening Jiang,et al.
Car Plate Recognition System
,
2012,
2012 Fifth International Conference on Intelligent Networks and Intelligent Systems.
[5]
Dana H. Ballard,et al.
Computer Vision
,
1982
.
[6]
İsmail Irmakçı.
Otomatik araç plaka tanıma sistemi
,
2008
.
[7]
Christopher M. Bishop,et al.
Neural networks for pattern recognition
,
1995
.