Manual wafer-level die inking is a common procedure for excluding die locations that are likely to be defective. Although this is a more cost-effective process, as compared to the expensive burn-in tests, it remains a labor-intensive step during IC testing. For each manufactured wafer, test engineers have to visually inspect every failure map in order to identify any regions where additional die need to be marked and discarded. Towards reducing this cost, we introduce a novel pattern recognition methodology to learn and automatically generate the inking patterns from the failure maps, thus eliminating the need for human intervention. Effectiveness is demonstrated on an industrial set of manually inked wafers.