Project Synopsis

Project Synopsis Title of the Project: Automatic Number Plate Recognition Introduction Automatic number plate recognition (ANPR) is a mass surveillance method that uses optical character recognition on images to read license plates on vehicles. They are used by various police forces and also as a method of electronic toll collection on payper-use per-use roads and monitoring trac activity activity such as red light adherence in an intersection. ANPR can be used to store the images captured by the cameras as !ell as the te"t from the license plate. ANPR technology tends to be region-speci#c$ region-speci#c$ o!ing to plate variation from place to place.

Problem Statement

 This pro%ect implements automatic number plate e"traction by capturing capturing the image of the Number plate and performing locali&ation$ character segmentation and recognition using 'R.

Objective  The ob%ective of the pro%ect pro%ect is to successfully successfully locate standard ndian ndian number plate$ segment characters and recogni&e them given a car image.

Methodologies  The basic process process of Number Plate Recognition Recognition includes four main stages stages *. mage mage Ac+uisition Ac+uisition and PrePre-proc processing essing mage to be ac+uire ac+uired d using any available hard!are. These captured images are in R, format. Pre-processing Pre-processing is essential to enhance the input image !hich in turn reduces time comple"ity for locali&ation and segmentation of characters. t mainly involves series of #ltering and saturating the image to mae the re+uired region prominent. /inally$ /inally$ it involves i nvolves converting the image into gray scale and increasing the contrast. 0. 1icense 1icense plate locali&a locali&ation tion n this this stage$ the the location location of the license license plate is identi#ed and the output of this stage !ill be a sub-image that contains only the license plate. This is done in t!o main steps. Locating a large bounding rectangle over the license plate. Determining the exact location of the license plate. •  •

2. haracter haracter 3egmenta 3egmentation tion This stage stage is meant meant for segmentat segmentation ion of the characters from the plate. A precise binary image is got after the license plate locali&ation. n order to recogni&e the vehicle number plate characters after!ards$ after!ards$ each character must be divided respectively. respectively. That is tas of

character segmentation. The individual characters have to be distinguished (segmented) from each other. other. The output of this stage is a set of monochrome images for each character in the plate. 4.

haracter haracter Recogn Recognition ition haracter haracter recognit recognition ion step !ill !ill be identifying identifying the characteristics of the character input image. n this stage$ the segmented characters are rescaled to match the characters into a standard si&e. 5i6erent methods can used for character recognition. 'ne of the method for character recognition is the optical character recognition ('R) is used to compare the each individual character against the complete alphanumeric database. The 'R actually uses correlation method to match individual character and #nally the number7alphabet is identi#ed and stored .The character is then compared !ith the database for the vehicle authori&ation. The resultant signals are given according to the result of comparison.

Hardware and Software e!uirements 8ard!are • •

maging 8ard!are ( 5igital amera) 3ystem Re+uirements   9indo!s :P7;7<7*=  >, 5is 3pace  0, of RA?  ,raphics card supporting 'pen,1 2.2 !ith *, ,P@ memory recommended

3oft!are ?at1ab 0=**a or above

"pplications and #onclusion ANPR system has its application in number of areas • • • • •

Paring automation and security ehicular access control ?otor!ay Road Tolling Tolling order ontrol 1a! Bnforcement

n this Pro%ect$ automatic number plate recognition using vehicle license plate is implemented. The system utili&es image processing techni+ues for identifying the vehicle number. number. The system !ors satisfactorily for !ide variation of constraints and di6erent types of number plates. The system is to be implemented and e"ecuted in ?at1ab and performance is tested on genuine images.