Vehicle applied the any technique to real-time capture

number plate recognition has been an ongoing innovative research for over the
last few years. Many researches have been carried out to identify the different
type of vehicle such as a truck, car, bus or any four wheeler vehicle. In paper
14, the soble filter algorithm was used to address this issue to get the
edges of the vehicle which is applied to detect and recognize the type of
vehicle.  The model of 11 the vehicle
find out through in the use of SVM (Support Vector Machine) and contourlet
Transform. They showed many numerical results on data set of pictures. However,
they could not be applied the any technique to real-time capture of video
stream 2. In the paper 16 monocular images technique are used for car
recognition. They applied canny edge detection for detect edges to detect the
presence of vehicle and their number plate and SVM classifier to recognize the
vehicle number classification. In paper 12, recognition of the type of
vehicle irrespective of scale, size and rotation variation of vehicles number
plate where 7 we applied the filter, MACH filter and Log r-theta Mapping


In paper 18, OCR
techniques was used 5, which is a commonly used technology for optical
character recognition, which is used for translation of scanned images of
printed text into format of machine encoded text. Basically an OCR technique is
based on neural network fee-forward system. This is proposed for where two real
character images, which is no-overlapping to each other, sets of data uses for
training and training using neural network technology. ANN based neural network
system used for pattern recognition. ANN generally used feed-forward neural
network based intelligent computing architecture, which can be classify the inputs
into a set of target categories. Neural network done work well and can achieve
better performance to other even the size and color of number plate be
different it is also work under in the difficult environment.

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    I. System

The proposed
system contains various stages as image acquisition, pre-processing, number
plate localization, character segmentation, character recognition. The system
is designed in Matlab based GUI application.


A. Car Image
Captured By Camera

Arduino Uno
attached with the motion sensor which detect the motion of car. Then the motor
helps to rotate the camera for capturing the car images from real time videos
2. We use the high resolution picture quality camera for image acquisition,
identified is captured using high resolution digital camera.


B. Preprocessing

Firstly, we
convert the input RGB color image to a gray-scale images. To speed up the
process, the image is first downscaled to 50% of the original. Here mathematical morphology 6
is used to detect the plate region and the sobel operator are used for
calculation of the threshold value. After this system we will get a dilated
image. Then we use imfill function for fill the holes, so that we can get a
clear binary image.


Figure 2: A GUI layout
System overview of Indian Number Plate Recognition System


C. Indian
Number plate Localization

Pre-processing is
the important technique to filtering and edges detection. The image is
pre-processed, passing through gray scale filter and edge detection method is
applied. Which applied to the isolate of the plate region of interest.
Localization 1, 4 is an algorithmic function for identifying a number
plate. By the use of localizing determines the aspect ratio of number plate of
vehicle image. This
algorithm search the similar background coloursof  the image unified proportion and mean contrast
differentiate number plate objects on a vehicle.


(i) Edge Detection

There are many
methods of which performing edge detection of image. We detected the edges of
input image 6, here we using canny edge detector which used to takes a
gray-scale image as its input of this system, and then returns a binary image
of same size 11 as an output image, where the edge detection function finds
the edges in the input gray image.


(ii) Character

In the identified
number plate region where character are segmented using function of
region-props of Matlab, It is use to find the boxes bounding for each
characters. This function returns the smallest bounding box, which 13
contains a character. So, we can use this method for obtain the bounding boxes
of all character in vehicle number plate.


D. Character

Template matching
is a technique of character recognition. It is method of finding the fixed
location of a template (sub-image), which inside of captured image.  Template matching having similarities 12
between a given template image and windows with same size in an image and that
identifying the window, that produces highest similarity measure. It works with
pixel-by-pixel comparison and each possible pixel displacement of the template


E. Identify the
Stolen Car

The main purpose
of this state that recognize and classification of binary images that have
contains character which is received by previous stage. After doing this stage
each character must have a valid label and having an error factor. If this
error factor is greater than a predefined data value will be used for reject
the false characters which passed from previous one. For the time of
classification step some features must have collected data from the characters.
This is use for because image to text into characters conversion. In number plate each individual
character match from the completer alphanumeric database using template
matching method. The matching process is checked the template image to all
possible positions in a input larger image and computes a particular numerical
index which indicate that how the template is matches and what quality of
matches the image in that position. After template is matched we having
a valid vehicle number which is matches from the database of excel sheet
automatically. If the stolen vehicle is detect then the alert system will be on.
We can be recognize data using the internet. We store stolen vehicle database
in online database and connect to Matlab java connecter. 


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