Bayesian Super-Resolution of Text in Video with a Text-Specific Bimodal Prior

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.

• Type: Conference
• Year: 2005
• Where: CVPR
• Authors: Katherine Donaldson, Gregory K. Myers
• Keywords: Computer Vision, CVPR 2005, Piecewise Smoothness, Video Scene Text