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<!DOCTYPE HTML>
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<article class="box post">
<header class="style1">
<h2>Bits Visualized As Color</h2>
<p>BVAC data storage system</p>
</header>
<a href="#" class="image featured">
<img src="images/pic01.png" alt="" />
</a>
<h3>Introduction</h3>
<p>Concept: </br>
The current version of the BVAC
system (as of 4/19/21) represents
every possible combination of binary
in a file, as color in a photo. For
example, the current version has the
ability to represent two bits of
information for every pixel (We are,
as of time of writing, making a third
version, which will enable four bits of
information to be represented by a
single pixel), the way we do this is
quite simple, there are only four
possible combinations for two bits of
binary: 1 1, 1 0, 0 1, 0 0. So we have
four colors represent each possible
combination of these bits, in our case,
red represents 0 1, blue represents 1 0,
black represents 1 1, and white
represents 0 0. We then tell the wallets
of our blockchains to write to a .jpg
according to an array which can be
located in fractal/fractalbvac.cpp</p>
<h3>Evolution</h3>
<p>VERSION 3
Version Three of this system will involve storing four bits of information per pixel, as
some of you reading this may know, the formula for how many possible combinations
for an amount of bits, X, is equal to 2^X. For example, say we want to store 1 byte (8
bits) per pixel, the equation for how many possible combinations, and by extension how
many colors weβd need, is 2^8, which equals 256, so weβd need 256 colors to be able to
represent 1 byte per pixel. The reason as to why this is such a challenge for us will be
discussed in βChallengesβ. Though it is quite difficult to represent 8 bits per pixel, 4 - 6
bits is perfectly within our limit. How we do this, is by utilizing RGBA values in place
of regular RGB. By setting the absolute value of an alpha value to either 0 or 1, we then
double how many colors we can use. For those who donβt know what an alpha value is,
itβs the transparency of a color on a scale of 0 β 1. So, the possible combinations of
defined as 2^4 = 16:
1) 0000
2) 0001
3) 0010
4) 0011
5) 0100
6) 0101
7) 0110
8) 0111
9) 1000
10) 1001
11) 1010
12) 1011
13) 1100
14) 1101
15) 1110
16) 1111
We then simply assign an RGB value to half of these with their alpha value being 0,
then assign the other half with the exact same RGB values, but with an alpha value of 1.</p>
<h3>Challenges</h3>
<p>
The main challenge that weβve been
having to deal with would have to be Blueprint of the third iteration of the BVAC system.
the loss of pixel information due to the
compression of .jpg images. As a result, weβve had to stick to absolute values (either the
max or minimal value, a value can be) that way it doesnβt get in the way. If we wanted
to represent six bits of
information per pixel, then
weβd have to tie in a βmiddle
valueβ that isnβt the lowest a
value can be, and not the
highest a value can be. Then on
top of that, weβd have to tie in
alpha values as absolute
values like we did with
versions two and three.
If possible weβd like to use a
new image format to avoid
these issues and possible store
as many color combinations as
possible to represent as many
combinations of bits as
possible. However, it seems the .jpg is the most supported image file format, as a result
we canβt move to a new image format without the risk of secluding potential members
of the community.
Next, we will discuss the limits of the technology.</p>
<h3>Limits</h3>
<p>As we have discussed previously, the formula for how many possible combinations for
an array of binary is defined as:
2
π₯ = πππ π ππππ πΆπππππππ‘ππππ
Where x is equal to how many bits of potential information you want to store. So,first we calculate howThere are three values in an RGB value; Red, Green, and Blue. Each has an absolute
value of 255 and a minimal value of 0. Mathematically, we need to account for the lack
of color (0) as well, so we use 256 as a βrealβ interpretation to how many values can be
contained within each RGB value.
256 x 256 x 256 = 16,777,216.
So, we have 16,777,216 possible combinations of RGB values. We then adjust the
formula accordingly:
2
π₯ = 16,777,216 β 2
24 = 16,777,216
We have now proven that the maximum number of bits we can represent is 16,777,216
without use of Alpha values; However, there are two-hundred-fifty-six possible alpha
values for every color, so if we wanted to talk about the max limit of the system with
the inclusion of alpha values, weβd adjust the formula so:
2
π₯ = (256 β 256 β 256)256;
2
π₯ = 4,294,967,296
π₯ =
ππ(4,294,967,296)
ππ(2)
; π₯ = 32
For ease of use, we will limit this to 32 bits per pixel. To put into perspective how dense
this is, it is 4 bytes per pixel. My resume is 163,840 bits in size (20,480 bytes), we divide
that by 4 (because we can store 4 bytes per pixel) and we get 5,120β¦ we find the square
root of that, and we get 71.55 x 71.55, we will round that to 72 pixels. So, all we would
need is a 72x72 image!
</p>
<h3>The Future</h3>
<p>If one were to first obfuscate or encrypt a data string, convert it to binary, then store it
into string that gets stored as pixels, not only would you have a compression method,
but an encrypted, compression method, where the
data is stored locally in the BVAC code as
instructions. This has many applications ranging
from a method of block storage for blockchains for
additional security (unfortunately, at the probable
cost of disk space, at least until the consensus grows
wide enough for this to have any actual effect as a
compression method) to simply inventorying stuff
like lab equipment and chemicals. This could also be
used as a method of machine learning, as one could
dedicate an AI to crunching and storing information
as a BVAC code, both accomplishing educating the
AI, and storing the information it has processed.
To improve the BVAC system further, one can store
the resultants of compression algorithms to a BVAC
code, so that they may improve current compression
techniques, without having to worry about loss of
data. </p>
</article>
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The Espers Project<br />
444 S Cactus Junction<br />
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