Title :
Binarising camera images for OCR
Author :
Seeger, Mauritius ; Dance, Christopher
Author_Institution :
Xerox Res. Centre Eur., Cambridge, UK
fDate :
6/23/1905 12:00:00 AM
Abstract :
We describe a 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
Keywords :
image segmentation; image sensors; interpolation; optical character recognition; Niblack local average method; OCR; adaptive thresholding; background surface thresholding; binarisation method; camera images; lighting variations; low quality images; low resolution text; neighbouring background intensities; Algorithm design and analysis; Binary search trees; Degradation; Digital cameras; Error analysis; Europe; Feedback; Noise robustness; Optical character recognition software; Runtime;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953754