What is the best way to programmatically detect po

Question

Akismet does an amazing job at detecting spam comments. But comments are not the only form of spam these days. What if I wanted something like akismet to automatically detect porn images on a social networking site which allows users to upload their pics, avatars, etc?

There are already a few image based search engines as well as face recognition stuff available so I am assuming it wouldn't be rocket science and it could be done. However, I have no clue regarding how that stuff works and how I should go about it if I want to develop it from scratch.

How should I get started?

Is there any open source project for this going on?

Answer 1

If you're really have time and money:

One way of doing it is by 1) Writing an image detection algorithm to find whether an object is human or not. This can be done by bitmasking an image to retrieve it's "contours" and see if the contours fits a human contour.

2) Data mine a lot of porn images and use data mining techniques such as the C4 algorithms or Particle Swarm Optimization to learn to detect pattern that matches porn images.

This will require that you identify how a naked man/woman contours of a human body must look like in digitized format (this can be achieved in the same way OCR image recognition algorithms works).

Hope you have fun! :-)

Answer 2

short answer: use a moderator ;)

Long answer: I dont think there's a project for this cause what is porn? Only legs, full nudity, midgets etc. Its subjective.

Answer 3

I've seen a web filtering application which does porn image filtering, sorry I can't remember the name. It was pretty prone to false positives however most of the time it was working.

I think main trick is detecting "too much skin on the picture :)

Answer 4

BOOM! Here is the whitepaper containing the algorithm.

Does anyone know where to get the source code for a java (or any language) implementation?

That would rock.

One algorithm called WISE has a 98% accuracy rate but a 14% false positive rate. So what you do is you let the users flag the 2% false negatives, ideally with automatic removal if a certain number of users flag it, and have moderators view the 14% false positives.

Answer 5

Nude.js based on the whitepaper by Rigan Ap-apid from De La Salle University.

Answer 6

There is software that detects the probability for porn, but this is not an exact science, as computers can't recognize what is actually on pictures (pictures are only a big set of values on a grid with no meaning). You can just teach the computer what is porn and what not by giving examples. This has the disadvantage that it will only recognize these or similar images.

Given the repetitive nature of porn you have a good chance if you train the system with few false positives. For example if you train the system with nude people it may flag pictures of a beach with "almost" naked people as porn too.

A similar software is the facebook software that recently came out. It's just specialized on faces. The main principle is the same.

Technically you would implement some kind of feature detector that utilizes a bayes filtering. The feature detector may look for features like percentage of flesh colored pixels if it's a simple detector or just computes the similarity of the current image with a set of saved porn images.

This is of course not limited to porn, it's actually more a corner case. I think more common are systems that try to find other things in images ;-)