One-Shot Template Matching for Automatic Document Data Capture
TABLE I: The performance of our model.
['[BOLD] Field', '[BOLD] Accuracy', '[BOLD] Mean-Fuzzy-Match']
We can see that Mean-Fuzzy-Match is significantly greater than Accuracy, implying that our model can leverage better accuracy if the minor OCR errors are corrected by post-processing. For instance, the buyer and seller names can be matched with a lookup table. Similarly, dates and amounts can be canonicalized to eliminate format discrepancies. Other texts can be normalized by trimming whitespaces, converting to lowercase, and so on.