Crime Spotter

Inspiration:

Crimes committed by numerous people always flood newspapers and news channels. In order to contribute to society by reducing the crimes rates, we wanted to create something that can aid in catching criminals. Hence, we came up with crime spotter.

What it does:

Crime spotter is a software that we created reads the images captured in real time by a camera in a public place and compares to a database of criminals. If there is a match, it sends the information regarding the criminal, hence reducing the difficulty in tracking down criminals.

How we built it:

The software was coded in python which compared a live picture taken from a camera with the images of a potential suspect. By using a hog training model, we analyze peoples faces and find out how much they correlate with a target's facial features. By doing so, we are able to deploy a cheap and real-time facial detection module that can be added to existing security practices.

Challenges we ran into:

The first trouble we had run into was comparing the live images with the data images, as it was sometimes difficult to make out some features. The other problem we had faced was outputting the information of the criminal after matching the images with the database.

What's next for Crime Spotter:

Our aim is to go global as we aim to reduce crimes rates as much as possible. By using this technology, it is the first step towards a more safe society.