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The Ethereal
Fooling OCR Systems with Adversarial Text Images
February 15, 2018 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Congzheng Song, Vitaly Shmatikov
arXiv ID
1802.05385
Category
cs.LG: Machine Learning
Cross-listed
cs.AI,
cs.CR,
cs.CV
Citations
55
Venue
arXiv.org
Last Checked
5 months ago
Abstract
We demonstrate that state-of-the-art optical character recognition (OCR) based on deep learning is vulnerable to adversarial images. Minor modifications to images of printed text, which do not change the meaning of the text to a human reader, cause the OCR system to "recognize" a different text where certain words chosen by the adversary are replaced by their semantic opposites. This completely changes the meaning of the output produced by the OCR system and by the NLP applications that use OCR for preprocessing their inputs.
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