My users are uploading images to my website and i would like first to offer them already uploaded images first. My idea is to 1. create some kind of image "hash" of every existing image 2. create a hash of newly uploaded image and compare it with the other in the database
i have found some interesting solutions like http://www.pureftpd.org/project/libpuzzle or or http://phash.org/ etc. but they got one or more problems
I would be OK to find only VERY similar images (so e.g. different size, resaved jpg or different jpg compression factor).
The only idea I got is to resize the image to e.g. 5px*5px* 256 colors, create a string representation of it and then find the same. But I guess that it may have create tiny differences in colors even with just two same images with different size, so finding just the 100 % same would be useless.
So I would need some good format of that string representation of image which than could be used with some SQL function to find similar, or some other nice way. E.g. phash create perceptional hashes, so when two numbers are close, the images should be close as well, so i just need to find closest distances. But it is again external library.
Is there any easy way?
I've had this exact same issue before.
Feel free to copy what I did, and hopefully it will help you / solve your problem.
My first idea that failed, similar to what you may be thinking, is I ended up making strings for every single image (no matter what size). But I quickly worked out this fills your database super fast, and wasn't effective.
Next option (that works) was a smaller image (like your 5px
idea), and I did exactly that, but with 10px
*10px
images. The way I created the 'hash' for each image was the imagecolorat()
function.
When receiving the rgb
colours for the image, I rounded them to the nearest 50
, so that the colours were less specific. That number (50
) is what you want to change depending on how specific you want your searches to be.
for example:
// Pixel RGB
rgb(105, 126, 225) // Original
rgb(100, 150, 250) // After rounding numbers to nearest 50
After doing this to every pixel (10px
*10px
will give you 100 rgb()
's back), I then turned them into an array, and stored them in the database as base64_encode()
and serialize()
.
When doing the search for images that are similar, I did the exact same process to the image they wanted to upload, and then extracted image 'hashes' from the database to compare them all, and see what had matching rounded rgb
's.
The Bigger that 50
is in the rgb
rounding, the less specific your search will be (and vice versa).
If you want your SQL to be more specific, it may be better to store extra/specific info about the image in the database, so that you can limit the searches you get in the database. eg. if the aspect ratio is 4:3
, only pull images around 4:3
from the database. (etc)
It can be difficult to get this perfectly 5px
*5px
, so a suggestion is phpthumb. I used it with the syntax:
phpthumb.php?src=IMAGE_NAME_HERE.png&w=10&h=10&zc=1 // &w= width of your image // &h= height of your image // &zc= zoom control. 0:Keep aspect ratio, 1:Change to suit your width+height
Good luck mate, hope I could help.