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公开(公告)号：US10354161B2
公开(公告)日：2019-07-16
申请号：US15614298
申请日：2017-06-05
Applicant: INTUIT INC.
Inventor： Peijun Chiang , Vijay Yellapragada
Abstract: The present disclosure relates to optical character recognition, and more specifically techniques for detecting font size in a digital image. Accordingly to one embodiment, a client device receives a digital image of a document having one or more textual components. The client device finds one or more contours bounding the one or more textual components in the digital image of the document. The client device detects a font size for text contained in the digital image using the one or more contours. The client device extracts the text from the digital image upon detecting that the detected font size is above a defined threshold value.
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公开(公告)号：US10229315B2
公开(公告)日：2019-03-12
申请号：US15221057
申请日：2016-07-27
Applicant: INTUIT INC.
Inventor： Vijay Yellapragada , Peijun Chiang , Sreeneel K. Maddika
Abstract: Aspects of the present disclosure provide methods and apparatuses for detecting duplicate copies of a form in an image of a document. An exemplary method generally includes obtaining a first digital image of a document, performing one or more transformations on the first digital image, determining one or more rectangles in the transformed first digital image, identifying at least a first duplicate copy of the form being depicted in the first digital image based, at least in part, on the detected one or more rectangles, and generating, based on the identified duplicate copy of the form, a notification that the first digital image includes at least the first duplicate copy of the form.
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Patent Agency Ranking
公开(公告)号：US10257375B2
公开(公告)日：2019-04-09
申请号：US15623008
申请日：2017-06-14
Applicant: INTUIT INC.
Inventor： Vijay Yellapragada , Peijun Chiang , Daniel Lee , Jason Hall , Shailesh Soliwal
IPC: H04N1/00 , H04N1/195 , H04N101/00
Abstract: Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, determining a type of the document, loading one or more pre-defined metrics associated with the document based on the determined type of the document, determining one or more characteristics of the document based on one or more analyses performed on the plurality of digital images of the document, comparing the one or more characteristics of the document with the one or more pre-defined metrics, and determining the document to be a long document based, at least in part, on the comparison.
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公开(公告)号：US10171695B1
公开(公告)日：2019-01-01
申请号：US15623113
申请日：2017-06-14
Applicant: INTUIT INC.
Inventor： Vijay Yellapragada , Peijun Chiang , Daniel Lee , Jason Hall , Shailesh Soliwal
Abstract: Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, segmenting at least a first digital image of the plurality of images into pixels associated with a foreground of the first digital image and pixels associated with a background of the first digital image, detecting a plurality of contours in the segmented first digital image, deciding, for each detected contour of the plurality of contours, whether that contour is an open contour or a closed contour, and determining that one or more sides of the document is out-of-bounds based, at least in part, on the decisions.
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公开(公告)号：US10163007B2
公开(公告)日：2018-12-25
申请号：US15499666
申请日：2017-04-27
Applicant: INTUIT INC.
Inventor： Daniel Lee , Vijay Yellapragada , Shailesh Soliwal , Peijun Chiang
Abstract: The present disclosure relates to the extraction of text from an image including a depiction of a document. According to one embodiment, a mobile device receives an image depicting a document. The mobile device identifies a plurality of text areas in the document and identifies a midpoint of each of the plurality of text areas in the document. The mobile device detects one or more lines of text in the document including a plurality of text areas, where the plurality of text areas included in a line of text are associated with a midpoint having a coordinate within a threshold number of pixels on one axis in a two-dimensional space. Based on an orientation of the detected one or more lines of text, the mobile device determines a probable orientation of the document and extracts text from the image based on the determined probable orientation of the document.
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公开(公告)号：US10210384B2
公开(公告)日：2019-02-19
申请号：US15218907
申请日：2016-07-25
Applicant: INTUIT INC.
Inventor： Vijay Yellapragada , Peijun Chiang , Sreeneel K. Maddika
Abstract: The present disclosure relates to optical character recognition using captured video. According to one embodiment, using a first image in stream of images depicting a document, the device extracts text data in a portion of the document depicted in the first image and determines a first confidence level regarding an accuracy of the extracted text data. If the first confidence level satisfies a threshold value, the device saves the extracted text data as recognized content of the source document. Otherwise, the device extracts the text data from the portion of the document as depicted in one or more second images in the stream and determines a second confidence level for the text data extracted from each second image until identifying one of the second images where the second confidence level associated with the text data extracted from the identified second image satisfies the threshold value.
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公开(公告)号：US10013643B2
公开(公告)日：2018-07-03
申请号：US15219888
申请日：2016-07-26
Applicant: INTUIT INC.
Inventor： Vijay Yellapragada , Peijun Chiang , Sreeneel K. Maddika
CPC classification number: G06K9/6267 , G06K9/00442 , G06K9/00449 , G06K9/00463 , G06K9/6256 , G06K2209/01 , G06Q40/123 , G06T7/11 , G06T2207/20081 , G06T2207/30176
Abstract: Techniques are disclosed for facilitating optical character recognition (OCR) by identifying one or more regions in an electronic document to perform the OCR. For example a method for identifying information in an electronic document includes obtaining a set of training documents for each template of a plurality of templates for the electronic document, extracting spatial attributes for at least a first label region and at least a first corresponding value region from the set, and training a classifier model based on the extracted spatial attributes, wherein the classifier model is used to identify the information in the electronic document. The spatial attributes represent a position of at least the first label region and at least the first value region within the electronic document.
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