Coded by Tejas K Aug 2017

Automatic-NPR-using-unique-Edge-Detection-Algorithm-and-Smarter-Analysis-Through-IoT

Automatic ANPR systems have been developed by pioneer researchers in the past. Hence, when we started this project we had two major obectives in our mind:

1. To improve the results by reducing the number of false positives encountered during the practical implementation of the program. We aimed to develop a robust algorithm which can detect the numberplates under various influencial factors such as weather, night lights or broken number plates.
2. To develop an unique prototype as to how this program can be implemented in the real world scenario and avail maximum benefits to the society by uniting all the servers over a city to behave as one unit embedded system using IoT protocols.

Both these objectives were achieved. A clear explanation to how the work was done is explained in the paper uploaded. This work was published in "AISC series of SPRINGER Journal" and was my 3rd research paper. Kindly, cite the paper if you have used the code/idea.

The OCR code is not uploaded since the raw characters cannot be uploaded due to privacy issues. It is recommended to go through the "Emotion Recognition" code in my Github profile which is very similar to the character recognition code.

For any further doubts, feel free to contact me over tejastk.reddy@gmail.com.