Which image metrics to use for selecting representative images from large image sets?
Posted: 2016-01-29T07:24:05-07:00
For example when selecting nice images for preview image montages of videos, movies (thumbnails, contact sheets, etc):
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Currently I extract about 1500 images equidistantly from a 1.5 hour video, and I calculate the following metrics for every images.
entropy:
number of unique colours:
standard deviation:
canny edge detector metric:
and last but not least the jpeg file size in bytes.
Then I normalize all of those data series to the 0.0-1.0 interval, and finally I calculate their root mean square (RMS). I normalize the RMS values as well into the 0.0-1.0 interval. Then I simply sort the images in reverse order according to the calculated RMS value, and I select the needed number of images by hand from the first part of the list...
What other image metrics and selecting methods should I consider to automate this process even further, possibly fully automatic?
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Currently I extract about 1500 images equidistantly from a 1.5 hour video, and I calculate the following metrics for every images.
entropy:
Code: Select all
identify -format "%[entropy]" 000001.jpg
Code: Select all
identify -format "%k" 000001.jpg
Code: Select all
convert 000001.jpg -format "%[fx:standard_deviation]" info:
Code: Select all
convert 000001.jpg -colorspace gray -canny 0x1+15%+40% -format "%[fx:mean]" info:
Then I normalize all of those data series to the 0.0-1.0 interval, and finally I calculate their root mean square (RMS). I normalize the RMS values as well into the 0.0-1.0 interval. Then I simply sort the images in reverse order according to the calculated RMS value, and I select the needed number of images by hand from the first part of the list...
What other image metrics and selecting methods should I consider to automate this process even further, possibly fully automatic?
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