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Bayesian super-resolution of text in videowith a text-specific bimodal prior

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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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Authors and Affiliations

  1. SRI International, 333 Ravenswood Avenue, 94025, Menlo Park, CA, USA

    Katherine Donaldson & Gregory K. Myers

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  1. Katherine Donaldson
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  2. Gregory K. Myers
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Donaldson, K., Myers, G.K. Bayesian super-resolution of text in videowith a text-specific bimodal prior. IJDAR 7, 159–167 (2005). https://doi.org/10.1007/s10032-004-0139-y

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  • DOI: https://doi.org/10.1007/s10032-004-0139-y

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