  Automatic License Plate Recognition (ALPR) is a challenging problem to the
research community due to its potential applicability in the diverse
geographical condition over the globe with varying license plate parameters.
Any ALPR system includes three main modules, viz. localization of the license
plate, segmentation of the characters therein and recognition of the segmented
characters. In real life applications where the images are captured over days
and nights in an outdoor environment with varying lighting and weather
conditions, varying pollution level and wind turbulences, localization,
segmentation and recognition become challenging tasks. The tasks become more
complex if the license plate is not in conformity with the standards laid by
corresponding Motor Vehicles Department in terms of various features, e.g. area
and aspect ratio of the license plate, background color, foreground color,
shape, number of lines, font face/ size of characters, spacing between
characters etc. Besides, license plates are often dirty or broken or having
scratches or bent or tilted at its position. All these add to the challenges in
developing an effective ALPR system.
