04-17-2025, 11:22 AM
Hi all. 
When I develop my NeuroLab program, I try to find ways to reduce the number of SB-neurons that are required for the program to function properly.
I was looking for a way that can find FEATURES in the information contained in an image on a 10x10 pixel matrix.
And today, an interesting idea came into my head.
Imagine this picture:
What happens if you expand the pixel matrix into one row? Then, "roll" this line into a ring, connecting the beginning of the line with its end.
Let this be the TEMPLATE of the figure "Cross", which we saved in the memory of the "SB-neural network".
Now, if we draw the same “Cross” on the “SB-display” of the “NeuroLab” program, but located in a different place of the matrix, then we can also “roll up” the data row of this matrix into a ring.
Let's now place both rings next to each other so that the "Template" is positioned ABOVE the new image.
Let first the pixel numbers of the “Template” and the new image coincide vertically. That is, the first pixel of the "Template" is located ABOVE the first pixel of the new image.
Now, we will count how many times the color of the "Template" pixel matches the color of the pixel of the new image located directly below it and write down this result.
After this, we shift (rotate) the lower ring with data by one pixel so that the second pixel of the new image is located under the first pixel of the "Template".
We will count the number of matches again and write down the result again.
We repeat this operation until the lower ring makes a "full turn" and the first pixel of the "Template" is ABOVE the last pixel of the new image.
Now, if we look at the records we made, we will surely see that the MAXIMUM number of matches between the color of the "Template" pixels and the pixels of the new image will be when the data of the "lower ring" coincides in space with the data of the "upper ring" (Template).
But the most interesting thing for me is to see how the "coincidence graph" will look if the new image also contains a "Cross", but whose size DIFFERENT from the size of the "Cross" on the "Template".
Will the "FEATURES" of the "Cross" figure be able to manifest themselves in the form of local maxima on the "Chart of the number of coincidences" when the size and position of the two crosses do not match?
When I develop my NeuroLab program, I try to find ways to reduce the number of SB-neurons that are required for the program to function properly.
I was looking for a way that can find FEATURES in the information contained in an image on a 10x10 pixel matrix.
And today, an interesting idea came into my head.
Imagine this picture:
What happens if you expand the pixel matrix into one row? Then, "roll" this line into a ring, connecting the beginning of the line with its end.
Let this be the TEMPLATE of the figure "Cross", which we saved in the memory of the "SB-neural network".
Now, if we draw the same “Cross” on the “SB-display” of the “NeuroLab” program, but located in a different place of the matrix, then we can also “roll up” the data row of this matrix into a ring.
Let's now place both rings next to each other so that the "Template" is positioned ABOVE the new image.
Let first the pixel numbers of the “Template” and the new image coincide vertically. That is, the first pixel of the "Template" is located ABOVE the first pixel of the new image.
Now, we will count how many times the color of the "Template" pixel matches the color of the pixel of the new image located directly below it and write down this result.
After this, we shift (rotate) the lower ring with data by one pixel so that the second pixel of the new image is located under the first pixel of the "Template".
We will count the number of matches again and write down the result again.
We repeat this operation until the lower ring makes a "full turn" and the first pixel of the "Template" is ABOVE the last pixel of the new image.
Now, if we look at the records we made, we will surely see that the MAXIMUM number of matches between the color of the "Template" pixels and the pixels of the new image will be when the data of the "lower ring" coincides in space with the data of the "upper ring" (Template).
But the most interesting thing for me is to see how the "coincidence graph" will look if the new image also contains a "Cross", but whose size DIFFERENT from the size of the "Cross" on the "Template".
Will the "FEATURES" of the "Cross" figure be able to manifest themselves in the form of local maxima on the "Chart of the number of coincidences" when the size and position of the two crosses do not match?
![[-]](https://litdev.uk/mybb/images/collapse.png)