An algorithm for mobile vision-based localization of skewed nutrition labels that maximizes specificity - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 235

penalty of this method could be quite high, it could allow for the detection and dewarping of
oddly shaped NLs. Finally, a more careful analysis of the found Hough lines during the early
rotation correction could allow us to detect and localize NLs of all possible rotations, not just
skewed ones.
The U.S. Food and Drug Administration recently proposed some changes to the design of
NLs on product packages [ 15 ] . The new design is expected to change how serving sizes are
calculated and displayed. Percent daily values are expected to shift to the left side of the NL,
which allegedly will make them easier to read. The new design will also require information
about added sugars as well as the counts for Vitamin D and potassium. We would like to em-
phasize that this redesign, which is expected to take at least 2 years, will not impact the pro-
posed algorithm, because the main tabular components of the new NL design will remain the
same. The nutritional information in the new NLs will still be presented textually in rows and
columns. Therefore, the corner and line detection and their projections will work as they work
on the current NL design [ 16 ] .
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