Suppose you're designing a software tool for identifying similar images. Discuss how you would adapt algorithms for the longest common substring problem to compare image data and find common features.
- By comparing the image sizes without analyzing the actual content.
- By converting image data into a format suitable for string comparison and applying longest common substring algorithms.
- By focusing only on the overall color distribution in the images.
- By randomly selecting pixels in the images for substring comparison.
Adapting longest common substring algorithms for image comparison involves converting image data into a format suitable for string comparison. This allows for the identification of common features by analyzing substrings within the image data.
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