Efficient Licence Plate Detection By Unique Edge Detection Algorithm and Smarter Interpretation Through IoT
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.
- Pub Date:
- October 2017
- Computer Science - Neural and Evolutionary Computing
- Paper has been submitted to SocPros17, 7th international conference on soft computing and problem solving, Scopus indexed. If accepted paper will be published in AISC series SPRINGER. Some of the extended/modified selected quality papers will be published in a Special Issue of 'Swarm and Evolutionary Computation journal, Elsevier (SCI). 10 pages