Extracting card data with card models
    3.
    发明授权
    Extracting card data with card models 有权
    使用卡片型号提取卡片数据

    公开(公告)号:US08831329B1

    公开(公告)日:2014-09-09

    申请号:US14059151

    申请日:2013-10-21

    Applicant: Google Inc.

    Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.

    Abstract translation: 这里的实施例提供了计算机实现的技术,用于允许用户计算设备使用光学字符识别(“OCR”)提取金融卡信息。 可以通过对图像数据应用各种分类器和其他变换来提高金融卡信息的提取。 例如,在应用OCR算法之前,对图像应用线性分类器以确定数字位置允许用户计算设备使用较少的处理能力来提取准确的卡数据。 OCR应用程序可以训练分类器来使用卡的磨损模式来改善OCR算法性能。 OCR应用可以应用线性分类器,然后应用非线性分类器来提高OCR算法的性能和准确性。 OCR应用程序使用典型的信用卡和借记卡使用的已知数字模式来提高OCR算法的准确性。

    EXTRACTING CARD DATA WITH CARD MODELS
    7.
    发明申请
    EXTRACTING CARD DATA WITH CARD MODELS 有权
    用卡片模型提取卡片数据

    公开(公告)号:US20150003719A1

    公开(公告)日:2015-01-01

    申请号:US14461001

    申请日:2014-08-15

    Applicant: GOOGLE INC.

    Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.

    Abstract translation: 这里的实施例提供了计算机实现的技术,用于允许用户计算设备使用光学字符识别(“OCR”)提取金融卡信息。 可以通过对图像数据应用各种分类器和其他变换来提高金融卡信息的提取。 例如,在应用OCR算法之前,对图像应用线性分类器以确定数字位置允许用户计算设备使用较少的处理能力来提取准确的卡数据。 OCR应用程序可以训练分类器来使用卡的磨损模式来改善OCR算法性能。 OCR应用可以应用线性分类器,然后应用非线性分类器来提高OCR算法的性能和准确性。 OCR应用程序使用典型的信用卡和借记卡使用的已知数字模式来提高OCR算法的准确性。

    Extracting card data with card models
    8.
    发明授权
    Extracting card data with card models 有权
    使用卡片型号提取卡片数据

    公开(公告)号:US09536160B2

    公开(公告)日:2017-01-03

    申请号:US14991516

    申请日:2016-01-08

    Applicant: GOOGLE INC.

    Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.

    Abstract translation: 这里的实施例提供了计算机实现的技术,用于允许用户计算设备使用光学字符识别(“OCR”)提取金融卡信息。 可以通过对图像数据应用各种分类器和其他变换来提高金融卡信息的提取。 例如,在应用OCR算法之前,对图像应用线性分类器以确定数字位置允许用户计算设备使用较少的处理能力来提取准确的卡数据。 OCR应用程序可以训练分类器来使用卡的磨损模式来改善OCR算法性能。 OCR应用可以应用线性分类器,然后应用非线性分类器来提高OCR算法的性能和准确性。 OCR应用程序使用典型的信用卡和借记卡使用的已知数字模式来提高OCR算法的准确性。

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