Bayesian super-resolution of text in video with a text-specific bimodal prior

被引:15
|
作者
Donaldson K. [1 ]
Myers G.K. [1 ]
机构
[1] SRI International, Menlo Park, CA 94025
关键词
OCR; Super-resolution; Video;
D O I
10.1007/s10032-004-0139-y
中图分类号
学科分类号
摘要
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 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. © Springer-Verlag 2005.
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页码:159 / 167
页数:8
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