Showing too much 'skin' detection in software

Question

I am building an ASP.NET web site where the users may upload photos of themselves. There could be thousands of photos uploaded every day. One thing my boss has asked a few time

Answer 1

Of course, this will fail for the first user who posts a close-up of someone's face (or hand, or foot, or whatnot). Ultimately, all these forms of automated censorship will fail until there's a real paradigm-shift in the way computers do object recognition.

I'm not saying that you shouldn't attempt it nontheless; but I want to point to these problems. Do not expect a perfect (or even good) solution. It doesn't exist.

Answer 2

CrowdSifter by Dolores Labs might do the trick for you. I read their blog all the time as they seem to love statistics and crowdsourcing and like to talk about it. They use amazon's mechanical turk for a lot of their processing and know how to process the results to get the right answers out of things. Check out their blog at the very least to see some cool statistical experiments.

Answer 3

Perhaps the Porn Breath Test would be helpful - as reported on Slashdot.

Answer 4

Rigan Ap-apid presented a paper at WorldComp '08 on just this problem space. The paper is allegedly here, but the server was timing out for me. I attended the presentation of the paper and he covered comparable systems and their effectiveness as well as his own approach. You might contact him directly.

Answer 5

Your best bet is to deal with the image in the HSV colour space (see here for rgb - hsv conversion). The colour of skin is pretty much the same between all races, its just the saturation that changes. By dealing with the image in HSV you can simply search for the colour of skin.

You might do this by simply counting the number of pixel within a colour range, or you could perform region growing around pixel to calculate the size of the areas the colour.

Edit: for dealing with grainy images, you might want to perform a median filter on the image first, and then reduce the number of colours to segment the image first, you will have to play around with the settings on a large set of pre-classifed (adult or not) images and see how the values behave to get a satisfactory level of detection.

EDIT: Heres some code that should do a simple count (not tested it, its a quick mashup of some code from here and rgb to hsl here)

Bitmap b = new Bitmap(_image);
BitmapData bData = b.LockBits(new Rectangle(0, 0, _image.Width, _image.Height), ImageLockMode.ReadWrite, b.PixelFormat);
byte bitsPerPixel = GetBitsPerPixel(bData.PixelFormat);
byte* scan0 = (byte*)bData.Scan0.ToPointer();

int count;

for (int i = 0; i < bData.Height; ++i)
{
    for (int j = 0; j < bData.Width; ++j)
    {
        byte* data = scan0 + i * bData.Stride + j * bitsPerPixel / 8;

        byte r = data[2];
        byte g = data[1];
        byte b = data[0];

        byte max = (byte)Math.Max(r, Math.Max(g, b));
        byte min = (byte)Math.Min(r, Math.Min(g, b));

        int h;

        if(max == min)
            h = 0;
        else if(r > g && r > b)
            h = (60 * ((g - b) / (max - min))) % 360;
        else if (g > r && g > b)
            h = 60 * ((b - r)/max - min) + 120;
        else if (b > r && b > g)
            h = 60 * ((r - g) / max - min) + 240;


        if(h > _lowerThresh && h < _upperThresh)
            count++;
    }
}
b.UnlockBits(bData);

Answer 6

I would say your answer lies in crowdsourcing the task. This almost always works and tends to scale very well.

It doesn't have to involve making some users into "admins" and coming up with different permissions - it can be as simple as to enable an "inappropriate" link near each image and keeping a count.