Automatic Number Plate Recognition or in short (ANPR) was first invented in year 1976 at the Police Scientific Development Branch in the UK. With the improvement of digital camera and with the increase in computational capacity it gained much interest during the last decade.
Here the phenomena used are first to extract the image from the car body and recognize the letters and numbers printed on the plate. Now a day a digital camera is used with a moderate pixel or an average or good quality frame grabber to capture the image. Next the location of the number plate in the image is found and then extracts the characters for character recognition tool to translate the pixels into numerically readable character.
ANPR can be used in many areas from
1) Speed enforcement
2) Tool collection to management of parking lots, bridges or highways.
3) To detect and prevent a wide range of criminal activities
4) For security control of a highly restricted areas like military zones or area around top government offices.
The system is computationally inexpensive compare to the other ANPR systems
Besides the robustness, the earlier methods use either feature based approached using edge detection or Hough transform which are computationally expensive or use artificial neural network which requires large training data.
This ANPR system is designed in such a way so that it can be run real time and recognizes standard number of plate BANGLADESH under normal conditions.
The ANPR system works in three steps:
1) The car is being detected and an image is captured
2) From that image the car number plate is being detected and extracted
3) Required plate is then segmented horizontally and vertically using matlab codes to get individual character and at last using (OCR) to recognize the individual character with the help of database stored for each and every alphanumeric character.
Character used in number plates:
Numbers used in number plate:
Some information about bangla character:
The writing style of Bangla is from left to right comprising of 11 vowels and 39 consonant characters. These characters may be called as the basic characters. The concept of upper/lower case is absent in Bangla script. From Fig. 1 it is noted that most of the characters have a horizontal line at the upper level. This horizontal line is called head line. In Bangla language, we call it ‘matra’.
But we don’t need to deal with so many characters of bangla. We will only deal with the first letter and the last letter of the first line because other letters are common to all number plates. And for numbers we need to find all the numbers.
SYSTEM MODEL:
The overall ANPR system can be subdivided into
1) Software model
2) Hardware model.
Both models are discussed in detail.
1) Software Model
The main and the most important portion of this system is the software model. The software model use series of image processing techniques which are implemented in MATLAB 7.0.1.
The ANPR algorithm is broadly divided into three parts:
•Capture image
•Extract the plate from the image
•Recognize the numbers from the extracted plate
The first step is the capturing of an image using the USB camera connected to the PC. The images are captured in RGB format so it can be further process for the number plate extraction.
The second step of the ANPR algorithm is the extraction of the number plate in an image.
The third step of the developed ANRP algorithm uses Optical Character Recognition (OCR) algorithm to recognize the vehicle number. The resultant cropped image obtained after the second step is inverted i.e. all white pixels are converted to black and black pixels to white. Now the text is in white and the plate background is black. Before applying the OCR the individual lines in the text are separated using line separation process. The line separation adds the each pixels value in a row. If the resultant sum of row is zero that means no text pixel is present in a row and if the resultant sum of row is greater than zero that means the text is present in row. The first resultant sum greater than zero represents the start of the line and after this the first resultant sum equal to zero represents the end of the line. The start and end values of the line is used to crop the first line in the text. The same process continues to separate the second line in the text.
Once the lines in an extracted vehicle number plate are separated, the line separation process is now applied column wise so that individual character can be separated. The separated individual characters are then stored in separate variables. The OCR is now used to compare the each individual character against the complete alphanumeric database. The OCR actually uses correlation method to match individual character and finally the number is identified and stored in string format in a variable. The string is then compared with the stored database for the vehicle authorization. The resultant signals are given according to the result of comparison.
2) Hardware Model
The hardware model consists of sensors to sense the presence of a vehicle, camera to capture the image, a motor with motor driver circuit to control the barrier on the entrance, PC on which algorithm is executed, and microcontroller for controlling the complete hardware of the ANPR system.
As the vehicle enters and settles in the field of the sensor, the infrared sensor sense a vehicle and gives a signal to the PC through microcontroller 89C51 to capture the image of the vehicle. The camera connected to the PC through USB port captures the image of a vehicle. The ANPR algorithm on a PC receives the image and performs the processing, which yields the vehicle number. This number is then compared to the authorized number to confirm it validity and finally provides signal to microcontroller to control the system hardware. If the
inputted plate contains the authorized number then the barrier on the entrance will be raised up using motor, green indication light will be switched on and ‘Access Granted’ will appears on the display, and if the inputted plate contains an unauthorized number then barrier will not be raised, red indication will be switched on and ‘Access Denied’ will appear on the display.
What happens in practical?
A special type of hardware and software components is needed for applying in automatic number plate detection. These components are used to proceeds an input graphical signal like static pictures or video sequences, and recognizes license plate characters from it.
In case of hardware part of the ANPR system a camera, image processor, camera trigger, communication and storage unit is needed.
The hardware trigger physically controls a sensor directly installed in a lane. Whenever the sensor detects a vehicle in a proper distance of camera, it activates a recognition mechanism.
On other hand we can use a software detection of an incoming vehicle, or continual processing of the sampled video signal. Software detection, or continual video processing may have more system resources, but it does not need additional hardware equipment, like the hardware trigger.
On this project a quality camera with a moderate pixel is used for taking some static snapshots of car to keep the project simple and all the snaps are taken in visible light spectrum.
To be noted “Normal camera should not be used for capturing snapshots in darkness or night, because it operates in a visible light spectrum”.
For other conditions the infrared camera in combination with an infrared illumination gives a better result. As under the illumination, plates that are made from reflexive material are much more highlighted than rest of the image. This fact makes detection of license plates much easier.
Steps are:
1)The snapshots are inserted into the personnel computer using a data cable connected with the camera.2) The image of the number plate is then cropped; copy and paste to paint then save by given a name. An individual folder is created and a name is given to that folder. That cropped image is then saved into that newly created folder.
3) A MATLAB function is opened and that folder is connected with the MATLAB function through the directories
No comments:
Post a Comment