51 lines
1.7 KiB
Markdown
51 lines
1.7 KiB
Markdown
# The ALGORITHM!!!
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The general idea is to make a filter/mask of each of the corresponding fonts,
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and attempt to match them to the given letter.
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## Scoring system
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The score each font will have will be based on the average color(`acolor`)
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underneath each font mask(might be different `acolor` for each mask).
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After obtaining the `acolor` for a mask, the score will be calculated
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as the sum of the different pixel scores.
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For a given pixel(`po` for the original image and `pm` for the mask, same position)
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its score will be calculated as follows:
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```
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S_p = | po - acolor | x (0.5 - pm)
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```
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it is assumed that the font mask is of values between `0..1` and made as a
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'white on black' text(so `1` is where the font is).
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The given score calculation will take into consideration color
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variations of where the letter should be, while also taking into
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consideration the fact that the background should be of different
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color.
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## Potential improvements
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Some potential improvements would be:
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- Only consider pixels in the font and their outline.
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This might be helpful, as it would mean we dont care
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about pixels that are too far away, but assuming a good bounding boxes,
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it probably wont give much better results(or at all).
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Additionally, it poses some questions of which pixels should be considered,
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as both the text and mask are anti-aliased(thus having "weak" pixels)
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- Increase the area around the font.
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This idea can make sure we are not looking too inwards,
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although it shouldn't matter since we are looking to classify from
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a predefined set and not search them randomly, thus the potentially
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good information missed shouldn't matter that much
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(i.e. all scores will be 0.1 lower but the correct font shall still be picked)
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