Optimizing OCR Accuracy for Bi-tonal, Noisy Scans of Degraded Arabic Documents

Acquiring foreign language from degraded hardcopy documents is of interest to military and border control applications. Bi-tonal image scans are desirable because file size is small. However, the nature of hardcopy degradations and the scanner or image enhancement software capabilities used directly affect the quality of the captured image and the extent of language acquisition. We applied a collection of manual treatments to hardcopy Arabic documents to develop a corpus of bi-tonal images. We then used this corpus in an exploratory study to derive conclusions about how bi-tonal images could be enhanced. This paper discusses the manually degraded Arabic document corpus, the image enhancement study, and the significant optical character recognition (OCR) improvements obtained with simple scanner driver adjustments.