US 2019/0171900 A1 · ITERATIVE RECOGNITION-GUIDED THRESHOLDING AND DATA EXTRACTION

Abstract

Techniques for binarization and extraction of information from image data are disclosed. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; subjecting the region of interest within a digital image to a plurality of thresholding and extraction iterations; and extracting data from some or all of the plurality of binarized images. Corresponding systems and computer program products are disclosed.

Claims20

Dependent claims

A computer-implemented method, comprising:

identifying a region of interest within a digital image;
generating a plurality of binarized images based on the region of interest, wherein some or all of the binarized images are generated using a different one of a plurality of binarization thresholds;
and
subjecting the region of interest within a digital image to a plurality of thresholding and extraction iterations;
extracting data from some or all of the plurality of binarized images;
wherein the extracted data comprises one or more connected components represented in the plurality of binarized images;
and
wherein one or more of the connected components overlap or are obscured by one or more unique background elements such that no single binarization threshold applied to a region encompassing the one or more connected components can identify the one or more of the connected components that overlap or are obscured by the one or more unique background elements.

5 more elements

A computer program product, comprising a non-transitory computer readable medium having embodied therewith computer readable program instructions configured to cause a processor, upon execution thereof, to:

identify, using the processor, a region of interest within a digital image;
generate, using the processor, a plurality of binarized images based on the region of interest, wherein some or all of the binarized images are generated using a different one of a plurality of binarization thresholds;
and
extract, using the processor, data from some or all of the plurality of binarized images;
wherein extracting the data from some or all of the plurality of binarized images comprises:
generating, using the processor, at least one sequence of candidate extraction results for each grouping of one or more connected components depicted within the region of interest;
determining, using the processor, an optimal extraction result within each sequence of candidate extraction results;
and
assembling, using the processor, all of the optimal extraction results into a single string of the one or more connected components;
and
wherein determining the optimal extraction result within each sequence of candidate extraction results comprises selecting, using the processor, one extraction result within each sequence of candidate extraction results so as to minimize intensity differences between the optimal extraction results assembled into the single string;
and
wherein at least some of the connected components are text characters.

10 more elements

Dependencies are inferred from the claim text.

Iterative recognition-guided thresholding and data extraction

Life of this patent

Iterative recognition-guided thresholding and data extraction

Life of this patent

Abstract

Claims20