Unsupervised text region identification
AssigneeOpen Text Holdings, Inc.
InventorAvishek Kumar Shaw
Life of this patent
Estimating the term…
Abstract
Systems and methods for text localization are provided. Various embodiments of the present technology provide systems and methods for an improved and unsupervised system and method for identifying regions of interest containing text within digital documents and images. The systems and methods address the challenges of accurate text localization by employing a unique process that combines a connected component algorithm with a kernel identification algorithm. This approach allows for the processing of various input formats, including single lines, paragraphs, and full pages, overcoming the limitations of prior art systems that often require line segmentation.
Claims18
A method of text localization, comprising:
- receiving an input image document containing textual information;
- identifying regions of interest on the input image document indicating locations on the image document where text may be present using a connected component algorithm;
- identify a potential kernel for each identified region of interest;
- applying the identified potential kernels to convert the input image to a binary image;
- identifying spaces among the regions of interest to determine gaps between potential words in the regions of interest based on the binary image;
- and
- identifying text in the input image document based on the determined gaps between potential words in the regions of interest.
A system for providing text localization, the system comprising:
- a processor;
- and
- a non-transitory computer readable medium storing instructions translatable by the processor, the instructions when translated by the processor perform:
- receiving an input image document containing textual information;
- identifying regions of interest on the input image document indicating locations on the image document where text may be present using a connected component algorithm;
- identify a potential kernel for each identified region of interest;
- applying the identified potential kernels to convert the input image to a binary image;
- identifying spaces among the regions of interest to determine gaps between potential words in the regions of interest based on the binary image;
- and
- identifying text in the input image document based on the determined gaps between potential words in the regions of interest.
A computer program product comprising a non-transitory computer readable medium storing instructions translatable by a processor, the instructions when translated by the processor perform, in an enterprise computing network environment:
- receiving an input image document containing textual information;
- identifying regions of interest on the input image document indicating locations on the image document where text may be present using a connected component algorithm;
- identify a potential kernel for each identified region of interest;
- applying the identified potential kernels to convert the input image to a binary image;
- identifying spaces among the regions of interest to determine gaps between potential words in the regions of interest based on the binary image;
- and
- identifying text in the input image document based on the determined gaps between potential words in the regions of interest.
Dependencies are inferred from the claim text.