Bayesian super-resolution of text in videowith a text-specific bimodal prior |
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Authors: | Katherine Donaldson Gregory K. Myers |
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Affiliation: | (1) SRI International, 333 Ravenswood Avenue, 94025 Menlo Park, CA, USA |
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Abstract: | 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. |
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Keywords: | Super-resolution OCR Video |
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