we propose a novel automated image quality
assessment method that predicts the degree of degradation
on OCR. Unlike other image quality assessment algorithms
which only deal with blurring, the proposed method quantifies
image quality degradation across several artifacts and
accurately predicts the impact on OCR error rate. We present
evaluation results on a set of machine-printed document images
which have been captured using digital cameras with
different degradations.