Method and system for optical character recognition of series of images
First Claim
1. A method, comprising:
- receiving, by a processing device, a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images;
performing optical character recognition (OCR) of the current image to produce an OCR text and a corresponding text layout;
associating, using a coordinate transformation, at least part of the OCR text with a first cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images;
identifying a first median string representing the first cluster of symbol sequences based on a first subset of images of the series of images;
identifying a first template field of a document template corresponding to the first cluster based on the first median string representing the first cluster and the text layout of the current image;
analyzing the symbol sequences from the first cluster to identify suitable symbol sequences, wherein the suitable symbol sequences satisfy first parameters of the first template field;
identifying, for the first cluster, a second-level median string representing the cluster of symbol sequences based on a plurality of the suitable symbol sequences; and
producing, using the second-level median string, a resulting OCR text representing at least a portion of the first template field of the original document.
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Accused Products
Abstract
Systems and methods for performing OCR of a series of images depicting text symbols. An example method comprises: receiving, by a processing device, a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images; performing optical symbol recognition (OCR) of the current image to produce an OCR text and a corresponding text layout; associating, using a coordinate transformation, at least part of the OCR text with a first cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images; identifying a first median string representing the first cluster of symbol sequences based on a first subset of images of the series of images; identifying a first template field of a document template corresponding to the first cluster based on the first median string representing the first cluster and the text layout of the current image; analyzing the symbol sequences from the first cluster to identify suitable symbol sequences, wherein the suitable symbol sequences satisfy first parameters of the first template field; identifying, for the first cluster, a second-level median string representing the cluster of symbol sequences based on a plurality of the suitable symbol sequences; producing, using the second-level median string, a resulting OCR text representing at least a portion of the first template field of the original document.
9 Citations
20 Claims
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1. A method, comprising:
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receiving, by a processing device, a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images; performing optical character recognition (OCR) of the current image to produce an OCR text and a corresponding text layout; associating, using a coordinate transformation, at least part of the OCR text with a first cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images; identifying a first median string representing the first cluster of symbol sequences based on a first subset of images of the series of images; identifying a first template field of a document template corresponding to the first cluster based on the first median string representing the first cluster and the text layout of the current image; analyzing the symbol sequences from the first cluster to identify suitable symbol sequences, wherein the suitable symbol sequences satisfy first parameters of the first template field; identifying, for the first cluster, a second-level median string representing the cluster of symbol sequences based on a plurality of the suitable symbol sequences; and producing, using the second-level median string, a resulting OCR text representing at least a portion of the first template field of the original document. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system, comprising:
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a memory; a processing device, coupled to the memory, the processing device configured to; receive, by a processing device, a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images; perform optical character recognition (OCR) of the current image to produce an OCR text and a corresponding text layout; associate, using a coordinate transformation, at least part of the OCR text with a first cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images; identify a first median string representing the first cluster of symbol sequences based on a first subset of images of the series of images; identify a first template field of a document template corresponding to the first cluster based on the first median string representing the first cluster and the text layout of the current image; analyze the symbol sequences from the first cluster to identify suitable symbol sequences, wherein the suitable symbol sequences satisfy first parameters of the first template field; identify, for the first cluster, a second-level median string representing the cluster of symbol sequences based on a plurality of the suitable symbol sequences; and produce, using the second-level median string, a resulting OCR text representing at least a portion of the first template field of the original document. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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19. A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a processing device, cause the processing device to:
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receive, by a processing device, a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images; performed optical character recognition (OCR) of the current image to produce an OCR text and a corresponding text layout; associate, using a coordinate transformation, at least part of the OCR text with a first cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images; identify a first median string representing the first cluster of symbol sequences based on a first subset of images of the series of images; identify a first template field of a document template corresponding to the first cluster based on the first median string representing the first cluster and the text layout of the current image; analyze the symbol sequences from the first cluster to identify suitable symbol sequences, wherein the suitable symbol sequences satisfy first parameters of the first template field; identify, for the first cluster, a second-level median string representing the cluster of symbol sequences based on a plurality of the suitable symbol sequences; and produce, using the second-level median string, a resulting OCR text representing at least a portion of the first template field of the original document. - View Dependent Claims (20)
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Specification