Back to results
US 9,256,795 B1Granted
Text entity recognition
AssigneeA9.com, Inc.
InventorsDouglas Ryan Gray, Xiaofan Lin, Arnab Sanat Kumar Dhua, Yu Lou
Life of this patent
Estimating the term…
Abstract
Various embodiments enable the identification of semi-structured text entities in an imager. The identification of the text entities is a relatively simple problem when the text is stored in a computer and free of errors, but much more challenging if the source is the output of an optical character recognition (OCR) engine from a natural scene image. Accordingly, output from an OCR engine is analyzed to isolate a character string indicative of a text entity. Each character of the string is then assigned to a character class to produce a character class string and the text entity of the string is identified based in part on a pattern of the character class string.
Claims18
A computer-implemented method, comprising:
- displaying an image, captured by a camera of a computing device, on a display element of the computing device;
- analyzing the image to locate a region of text in the image;
- recognizing text within the region with an optical character recognition (OCR) engine, the OCR engine providing an output of recognized text including characters grouped by one or more text lines;
- analyzing the one or more text lines to isolate a character string indicative of at least one of a phone number, an email address, or a uniform resource locator (URL), each character of the isolated character string being assigned to a character class to produce a character class string;
- based at least in part on a pattern of the character class string, determining a matching score for the isolated character string with respect to at least one of a phone number, an email address, or a URL, the isolated character string being identified as the at least one of a phone number, an email address, or a URL if the matching score is greater than a threshold score, wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value;
- determining an overlay template and respective functionality for the at least one of a phone number, an email address, or a URL;
- and
- displaying the isolated character string on the display element using the overlay template as an overlay element in a live field of view being captured by the camera, the overlay element including at least one user-selectable element enabling the respective functionality associated with the at least one of a phone number, an email address, or a URL to be performed.
5 more elements
A computer-implemented method, comprising:
- receiving an output from an optical character recognition (OCR) engine;
- analyzing the output to isolate a character string indicative of a text entity;
- assigning each character of the isolated character string to a character class to produce a character class string;
- and
- based at least in part on a pattern identified for the character class string, identifying the isolated character string as being the text entity, wherein the isolated character string is identified as the text entity in response to determining a matching score above a threshold for the isolated character string, the matching score being based at least in part on a number of edits made to the character class string, and wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value.
2 more elements
A computing device, comprising:
- a processor;
- a display screen;
- and
- memory including instructions that, when executed by the processor, cause the computing device to:
- receive an output from an optical character recognition (OCR) engine;
- analyze the output to isolate a character string indicative of a text entity;
- assign each character of the isolated character string to a character class to produce a character class string;
- and
- based at least in part on a pattern of the character class string, identify the isolated character string as being the text entity, wherein the isolated character string is identified as the text entity in response to determining a matching score above a threshold for the isolated character string, the matching score being based at least in part on a number of edits made to the character class string, and wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value.
6 more elements
A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to:
- receive an output from an optical character recognition (OCR) engine;
- analyze the output to isolate a character string indicative of a text entity;
- assign each character of the isolated character string to a character class to produce a character class string;
- and
- based at least in part on a pattern of the character class string, identify the isolated character string as being the text entity, wherein the isolated character string is identified as the text entity in response to determining a matching score above a threshold for the isolated character string, the matching score being based at least in part on a number of edits made to the character class string, and wherein determining the matching store comprises assigning costs to edits made to the character class string, wherein a cost associated with mistaking characters that are similar in appearance is small and the cost associated with mistaking characters that are relatively different in appearance is greater than a threshold value.
2 more elements
Dependencies are inferred from the claim text.