  Vehicles play a vital role in modern day transportation systems. Number plate
provides a standard means of identification for any vehicle. To serve this
purpose, automatic licence plate recognition system was developed. This
consisted of four major steps: Pre-processing of the obtained image, extraction
of licence plate region, segmentation and character recognition. In earlier
research, direct application of Sobel edge detection algorithm or applying
threshold were used as key steps to extract the licence plate region, which
does not produce effective results when the captured image is subjected to the
high intensity of light. The use of morphological operations causes deformity
in the characters during segmentation. We propose a novel algorithm to tackle
the mentioned issues through a unique edge detection algorithm. It is also a
tedious task to create and update the database of required vehicles frequently.
This problem is solved by the use of Internet of things(IOT) where an online
database can be created and updated from any module instantly. Also, through
IoT, we connect all the cameras in a geographical area to one server to create
a universal eye which drastically increases the probability of tracing a
vehicle over having manual database attached to each camera for identification
purpose.
