  License Plate Recognition (LPR) plays an important role on the traffic
monitoring and parking management. A robust and efficient method for enhancing
accuracy of license plate characters recognition based on K Nearest Neighbours
(K-NN) classifier is presented in this paper. The system first prepares a
contour form of the extracted character, then the angle and distance feature
information about the character is extracted and finally K-NN classifier is
used to character recognition. Angle and distance features of a character have
been computed based on distribution of points on the bitmap image of character.
In K-NN method, the Euclidean distance between testing point and reference
points is calculated in order to find the k-nearest neighbours. We evaluated
our method on the available dataset that contain 1200 sample. Using 70% samples
for training, we tested our method on whole samples and obtained 99% correct
recognition rate.Further, we achieved average 99.41% accuracy using
three/strategy validation technique on 1200 dataset.
