Optical receipt processing
    1.
    发明授权

    公开(公告)号:US11887070B2

    公开(公告)日:2024-01-30

    申请号:US18058408

    申请日:2022-11-23

    Applicant: GROUPON, INC.

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

    OPTICAL RECEIPT PROCESSING
    2.
    发明公开

    公开(公告)号:US20230162165A1

    公开(公告)日:2023-05-25

    申请号:US18058408

    申请日:2022-11-23

    Applicant: GROUPON, INC.

    CPC classification number: G06Q20/047 G06V30/40 G06V30/10

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

    Optical receipt processing
    3.
    发明授权

    公开(公告)号:US11538263B2

    公开(公告)日:2022-12-27

    申请号:US17115447

    申请日:2020-12-08

    Applicant: Groupon, Inc.

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

    Optical receipt processing
    4.
    发明授权

    公开(公告)号:US10891474B1

    公开(公告)日:2021-01-12

    申请号:US16254040

    申请日:2019-01-22

    Applicant: Groupon, Inc.

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

    OPTICAL RECEIPT PROCESSING
    5.
    发明公开

    公开(公告)号:US20240177123A1

    公开(公告)日:2024-05-30

    申请号:US18533584

    申请日:2023-12-08

    Applicant: GROUPON, INC.

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

    Optical receipt processing
    6.
    发明授权

    公开(公告)号:US10229314B1

    公开(公告)日:2019-03-12

    申请号:US15281517

    申请日:2016-09-30

    Applicant: Groupon, Inc.

    Abstract: Techniques for providing improved optical character recognition (OCR) for receipts are discussed herein. Some embodiments may provide for a system including one or more servers configured to perform receipt image cleanup, logo identification, and text extraction. The image cleanup may include transforming image data of the receipt by using image parameters values that optimize the logo identification, and performing logo identification using a comparison of the image data with training logos associated with merchants. When a merchant is identified, a second image clean up may be performed by using image parameter values optimized for text extraction. A receipt structure may be used to categorize the extracted text. Improved OCR accuracy is also achieved by applying on format rules of the receipt structure to the extracted text.

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