Proceedings ArticleDOI
Enhancement of document images from cameras
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TLDR
This work has 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.Abstract:
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.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.read more
Citations
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Journal ArticleDOI
Camera-based analysis of text and documents: a survey
TL;DR: A survey of application domains, technical challenges, and solutions for the analysis of documents captured by digital cameras, and some sample applications under development and feasible ideas for future development is presented.
Proceedings ArticleDOI
Progress in camera-based document image analysis
TL;DR: A survey of application domains, technical challenges and solutions for recognizing documents captured by digital cameras, and some sample applications under development and feasible ideas for future development is presented.
Patent
Low resolution OCR for camera acquired documents
TL;DR: This paper proposed a global optimization framework for optical character recognition (OCR) of low-resolution photographed documents that combines a binarization-type process, segmentation, and recognition into a single process.
Proceedings ArticleDOI
CamWorks: a video-based tool for efficient capture from paper source documents
William M. Newman,Christopher R. Dance,Alex S. Taylor,Stuart Taylor,Michael J. Taylor,T. Aldhous +5 more
TL;DR: The design and evaluation of CamWorks, a system that employs a video camera as a means of supporting capture from paper sources during reading and writing, shows substantially faster text capture than with flatbed scanning.
Proceedings ArticleDOI
Binarising camera images for OCR
TL;DR: A binarisation method designed specifically for OCR of low quality camera images: background surface thresholding or BST, which produces considerably fewer OCR errors than Niblack's local average method while also being more runtime efficient.
References
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Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
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TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
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A survey of thresholding techniques
TL;DR: This paper presents a survey of thresholding techniques and attempts to evaluate the performance of some automatic global thresholding methods using the criterion functions such as uniformity and shape measures.
Book ChapterDOI
Computer graphics—principles and practice
TL;DR: These are the short notes for a two hour tutorial on principles and practice of computer graphics and scientific visualization and they cannot completely replace the contents of the tutorial transparencies and slides since restrictions in space and print quality do not permit the inclusion of figures and example images.