As digital cameras become cheaper and more powerful, driven by the consumer digital photography market, we anticipate significant value in extending their utility as a general office peripheral by adding a paper scanning capability. The main technical challenges in realizing this new scanning interface are insufficient resolution, blur and lighting variations. We have developed an efficient technique for the recovery of text from digital camera images, which simultaneously treats these three problems, unlike other local thresholding algorithms which do not cope with blur and resolution enhancement.
The technique first performs deblurring by deconvolution, and then resolution enhancement by linear interpolation. We compare the performance of a threshold derived from the local mean and variance of all pixel values within a neighborhood with a threshold derived from the local mean of just those pixels with high gradient. We assess performance using OCR error scores.