Pedestrian Detection Using MATLAB

MATLAB is a tool that is being used in order to achieve image processing. It is one of the fields which are being used widely nowadays. Pedestrians are the people who walk on roads. Vehicles need to be stopped when there are pedestrians walking on the road. Sometimes due to lack of observations, the vehicles hit the pedestrians who walk on the roads which lead to severe accidents. In order to avoid such situations, the pedestrian detection using MATLAB application has been implemented. This will be one of the unique applications that can be implemented in real time world with ease.

In the world, most of the people lose their precious lives mainly due to road accidents.  Pedestrian recognition on the road is very essential in order to avoid lot of accidents that occurs. This application can also help in recognizing even the animals which pass on the roads. Sometimes accidents occur due to the vehicles which cross on the roads. When there are pedestrians or animals moving on the road there will be some sort of notifications given to the driver to stop the vehicle through the use of this application. The vehicles can be detected easily at night and day time easily through the use of this application. People can rely on this application in order to avoid accidents on the road. This application can help in reducing a lot of road accidents. It can help in creating transparency. The features that can be included in the pedestrian detection using MATLAB application are as follows:

  • Avoid accidents: This application can help in reducing lot road accidents that occur.
  • Save life: This application can help in saving lot of lives without any difficulty.
  • Reliability: This application is reliable in use.
  • User friendly: This application will be user friendly since the user interface will be simple and easy to understand even by the common man.

 

🔥19 Views

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.