Too much false positives

[scratcher28]

Tested it with a lot of images, in fact, too much false positives. The most of test images are flagged as nude. A lot of really nude images are flagged as normal.

[mattaereal]

Can you provide us the images you used to test it? Besides that, this is a proof of concept made only to give a speech at a security conference.

On Mon, Oct 7, 2013 at 8:07 AM, scratcher28 notifications@github.comwrote:

Tested it with a lot of images, in fact, too much false positives. The most of test images are flagged as nude. A lot of really nude images are flagged as normal.

— Reply to this email directly or view it on GitHubhttps://github.com/alcuadrado/pija/issues/1 .

Atte: Matías Aereal Aeón

[alcuadrado]

As @mattaereal mentioned, this is a proof of concept for a security conference. We just wanted to have something running ASAP to be able to demonstrate that stealing pron automatically in a massive way is possible.

Besides that, nude detection is a very active research field, and there is lots of material out there to improve the accuracy of this script. Some ideas that come to my mind at the moment:

• Improve the skin color detection algorithm. We use a very basic one.
• Combine the algorithm with other alternatives, and tune some parameters.
• Use a feature-detection based algorithm alongside with this.
• Take the file names and metadata into consideration for classifying the image/video as porn or not.

I hope this helps you. We may need to explain this better in the README.