Thanks all! Binomial distribution curve was exactly what I needed, I figured out the rest from there. Jedishrfu, simplifying the problem was a very useful point as well!
Thanks again!
Hi,
I am trying to write a function which would take two arguments:
-> number of bits (which are a binary 0 or 1 value) N
-> and acceptable number of mismatching bits M
The function would statistically determine the probability of having M or less mismatching bits when randomly generating two N...
Thanks a ton! I'll try the things you have pointed out, I'm sure at least one of them will work! The larger Reed Solomon field sounds exactly like what I need. Thanks again :)
I am trying to find or develop an algorithm that can take a 1024 (lets assume random) bit array (so 128 bytes) and, by adding some redundancy (making the final code more than 1024 bits long), make it capable of decoding the data with up to n random bits flipped. Important point is that it has...
The picture of the tag would be taken multiple times and it needs to be able to tell if it's the same tag. Because there will be minor imprecisions when taking separate photos, SHA-2 would not do it, as it would generate a completely different key for the images. A bit of error should be tolerable.
Thank you so much! That is very useful info :)
One last thing I'd like to ask: do you think it would be possible to create an algorithm to do this faster? The reason I posted in a maths forum in the first place is to really see how robust it might be - maybe someone will find a way. As long as...
The base image was a new type of hologram (as in security sticker type, not the 3d image type) that can have various random patters on it, sometimes resembling landscape. I'm not sure which one I used for this one (I have quite a few) so I can't give you an original image.
Thanks for the quick reply, mfb.
To elaborate on why, in my eyes, the task would be difficult, I have processed a small image with the criteria visually represented (which you can see here). The eight gray shades each represent a cluster. The white bordered circles are their centers. Lines...
Currently I am generating an ID from an image by using K-Means to separate brightness levels into 8 levels (clusters) and order them brightest to darkest. For each cluster I calculate:
1) Their center points as a percentage of image size (using average pixel coordinates)
2) Average distance of...