Quality Assurance (QA) plays a critical role in high volume document digitization projects by making sure that the specified quality standard is reached under cost and time constraints. This paper takes a systematic view on this issue by summarizing and abstracting related existing work: quality bottlenecks and technical solutions throughout the whole processing pipeline, including cataloging, capture, image analysis and recognition, and error cascading; various strategies to conduct cost-effective QA, such as combination of auto-QA and manual QA, batch QA, special QA user interface, and open source QA.
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