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Binarising Camera Images for OCR

Mauritius Seeger, Chris Dance
In this paper we describe a new binarisation method designed specifically for OCR of low quality camera images: Background Surface Thresholding or BST. This method is robust to lighting variations and produces images with very little noise and consistent stroke width. BST computes a "surface" of background intensities at every point in the image and performs adaptive thresholding based on this result. The surface is estimated by identifying regions of low- resolution text and interpolating neighbouring background intensities into these regions. The final threshold is a combination of this surface and a global offset. According to our evaluation BST produces considerably fewer OCR errors than Niblack's local average method while also being more runtime efficient.
"Binarising Camera Images for OCR", Mauritius Seeger and Christopher Dance, Proceeding of Sixth International Conference on Document Analysis and Recognition (ICDAR). September 10th-13th, 2001, Seattle, USA.


Binarising-camera-images-for-OCR.pdf (212.97 kB)