To increase the range of sizes of video scene text recognizable by optical character recognition (OCR), we developed a Bayesian super-resolution algorithm that uses a text-specific bimodal prior. We evaluated the effectiveness of the bimodal prior, compared with and in conjunction with a piecewise smoothness prior, visually and by measuring the accuracy of the OCR results on the variously super-resolved images. The bimodal prior improved the readability of 4- to 7-pixel-high scene text significantly better than bicubic interpolation, and increased the accuracy of OCR results better than the piecewise smoothness prior.
Bayesian super-resolution of text in video with a text-specific bimodal prior
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) ; 1 ; 1188-1195 vol. 1
2005-01-01
274813 byte
Conference paper
Electronic Resource
English
Non-Stationary Approximate Bayesian Super-Resolution using a Hierarchical Prior Model
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