  Most vehicle license plate recognition use neural network techniques to
enhance its computing capability. The image of the vehicle license plate is
captured and processed to produce a textual output for further processing. This
paper reviews image processing and neural network techniques applied at
different stages which are preprocessing, filtering, feature extraction,
segmentation and recognition in such way to remove the noise of the image, to
enhance the image quality and to expedite the computing process by converting
the characters in the image into respective text. An exemplar experiment has
been done in MATLAB to show the basic process of the image processing
especially for license plate in Malaysia case study. An algorithm is adapted
into the solution for parking management system. The solution then is
implemented as proof of concept to the algorithm.
