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    Payment card OCR with relaxed alignment
    61.
    发明授权
    Payment card OCR with relaxed alignment 有权
    支付卡OCR轻松对齐

    公开(公告)号：US09367754B2

    公开(公告)日：2016-06-14

    申请号：US14462711

    申请日：2014-08-19

    Applicant: GOOGLE INC.

    Inventor： Xiaohang Wang ,  Farhan Shamsi ,  Yakov Okshtein ,  Sanjiv Kumar ,  Henry Allan Rowley ,  Marcus Quintana Mitchell ,  Debra Lin Repenning ,  Alessandro Bissacco ,  Justin Scheiner ,  Leon Palm

    IPC: G06K9/00 ,  G06K9/32

    CPC classification number: G06K9/3283 ,  G06K9/00469 ,  G06K9/18 ,  G06K9/228 ,  G06K9/325 ,  G06K9/40 ,  G06K2009/363 ,  G06K2209/01

    Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.

    Abstract translation: 以轻松对准的方式提取金融卡信息包括接收卡的图像的方法，在图像的位置确定一个或多个边缘查找器区域，并识别一个或多个边缘查找器区域中的线。 该方法还识别由所识别的线的外插的交点形成的一个或多个四边形，确定一个或多个四边形的纵横比，并将确定的四边形的纵横比与预期的纵横比进行比较。 然后，该方法识别与预期宽高比匹配的四边形，并在整流模型上执行光学字符识别算法。 在图像中的多个卡上执行类似的方法。 比较每个卡的分析结果，提高数据的准确性。

    COMPARING EXTRACTED CARD DATA WITH USER DATA
    63.
    发明申请
    COMPARING EXTRACTED CARD DATA WITH USER DATA 有权
    使用用户数据比较提取的卡数据

    公开(公告)号：US20160132740A1

    公开(公告)日：2016-05-12

    申请号：US14504214

    申请日：2014-10-01

    Applicant: GOOGLE INC.

    Inventor： Xiaohang Wang ,  Farhan Shamsi ,  Sanjiv Kumar ,  Henry Allan Rowley ,  Marcus Quintana Mitchell

    IPC: G06K9/18 ,  G06K9/62

    CPC classification number: G06K9/186 ,  G06K7/10 ,  G06K9/00469 ,  G06K9/18 ,  G06K9/2054 ,  G06K9/228 ,  G06K9/6202 ,  G06K2209/01 ,  G06Q20/32 ,  G06Q20/3223 ,  G06Q20/3276 ,  G06Q20/34 ,  G06Q20/36 ,  H04N1/00307

    Abstract: Extracting card data comprises receiving, by one or more computing devices, a digital image of a card; perform an image recognition process on the digital representation of the card; identifying an image in the digital representation of the card; comparing the identified image to an image database comprising a plurality of images and determining that the identified image matches a stored image in the image database; determining a card type associated with the stored image and associating the card type with the card based on the determination that the identified image matches the stored image; and performing a particular optical character recognition algorithm on the digital representation of the card, the particular optical character recognition algorithm being based on the determined card type. Another example uses an issuer identification number to improve data extraction. Another example compares extracted data with user data to improve accuracy.

    Abstract translation: 提取卡数据包括由一个或多个计算设备接收卡的数字图像; 对卡的数字表示进行图像识别处理; 识别卡的数字表示中的图像; 将所识别的图像与包括多个图像的图像数据库进行比较，并确定所识别的图像与图像数据库中存储的图像匹配; 基于所识别的图像与所存储的图像匹配的确定来确定与所存储的图像相关联的卡类型并将卡类型与卡相关联; 以及对所述卡的数字表示执行特定光学字符识别算法，所述特定光学字符识别算法基于所确定的卡类型。 另一个例子是使用发行人识别号来改进数据提取。 另一个例子比较了提取的数据与用户数据，以提高准确性。

    Extracting card data from multiple cards
    65.
    发明授权
    Extracting card data from multiple cards 有权
    从多张卡中提取卡片数据

    公开(公告)号：US09152858B2

    公开(公告)日：2015-10-06

    申请号：US13931966

    申请日：2013-06-30

    Applicant: GOOGLE INC.

    Inventor： Xiaohang Wang ,  Jeff Huber ,  Farhan Shamsi ,  Yakov Okshtein ,  Sanjiv Kumar ,  Henry Allan Rowley ,  Marcus Quintana Mitchell ,  Debra Lin Repenning

    IPC: G06K9/00 ,  G06K9/32

    CPC classification number: G06K9/00469 ,  G06K9/00463 ,  G06K9/2063 ,  G06K9/3283 ,  G06K9/6201 ,  G06K2209/01

    Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.

    Abstract translation: 以轻松对准的方式提取金融卡信息包括接收卡的图像的方法，在图像的位置确定一个或多个边缘查找器区域，并识别一个或多个边缘查找器区域中的线。 该方法还识别由所识别的线的外插的交点形成的一个或多个四边形，确定一个或多个四边形的纵横比，并将确定的四边形的纵横比与预期的纵横比进行比较。 然后，该方法识别与预期宽高比匹配的四边形，并在整流模型上执行光学字符识别算法。 在图像中的多个卡上执行类似的方法。 比较每个卡的分析结果，提高数据的准确性。

    PREVENTING FRAUD USING CONTINUOUS CARD SCANNING
    67.
    发明申请
    PREVENTING FRAUD USING CONTINUOUS CARD SCANNING 审中-公开
    使用连续卡扫描预防欺诈

    公开(公告)号：US20150006387A1

    公开(公告)日：2015-01-01

    申请号：US14037063

    申请日：2013-09-25

    Applicant: GOOGLE INC.

    Inventor： Xiaohang Wang ,  Marcus Quintana Mitchell

    IPC: G06Q20/40 ,  G06K9/78

    CPC classification number: G06K9/6201 ,  G06K9/00201 ,  G06K9/00469 ,  G06K9/00483 ,  G06K9/03 ,  G06K9/036 ,  G06K9/18 ,  G06K9/20 ,  G06K9/2054 ,  G06K9/228 ,  G06K9/344 ,  G06K9/6202 ,  G06K9/78 ,  G06K2009/2045 ,  G06K2209/01 ,  G06K2209/40 ,  G06Q20/322 ,  G06Q20/327 ,  G06Q20/34 ,  G06Q20/4016 ,  G06T17/00

    Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

    Abstract translation: 比较来自连续扫描的提取的卡数据包括由一个或多个计算设备接收卡的数字扫描; 从所述物理卡的数字扫描中获取所述卡的多个图像; 对所述多个图像中的每一个执行光学字符识别算法; 比较针对所述多个图像中的每一个的所述光学字符识别算法的应用结果; 确定所述多个图像中的每一个的结果的配置阈值是否彼此匹配; 以及当多个图像中的每一个的结果彼此匹配时验证结果。 可以采用提取的卡数据的阈值置信水平来确定提取的准确性。 从混合图像和卡片的三维模型进一步提取数据。 图像中的压纹文字和全息图可能被用来防止欺诈。

    HIERARCHICAL CLASSIFICATION IN CREDIT CARD DATA EXTRACTION
    68.
    发明申请
    HIERARCHICAL CLASSIFICATION IN CREDIT CARD DATA EXTRACTION 有权
    信用卡数据提取中的分层分类

    公开(公告)号：US20150003748A1

    公开(公告)日：2015-01-01

    申请号：US14059071

    申请日：2013-10-21

    Applicant: GOOGLE INC.

    Inventor： Sanjiv Kumar ,  Henry Allan Rowley ,  Xiaohang Wang ,  Jose Jeronimo Moreira Rodrigues

    IPC: G06K9/00

    CPC classification number: G06K9/6269 ,  G06K9/00469 ,  G06K9/00536 ,  G06K9/18 ,  G06K9/186 ,  G06K9/3233 ,  G06K9/3258 ,  G06K9/46 ,  G06K9/6202 ,  G06K9/6267 ,  G06K9/66 ,  G06K2009/4666 ,  G06K2209/01 ,  G06Q20/227 ,  G06Q20/34 ,  G06T3/0012 ,  G06T7/11 ,  G06T2207/20132 ,  G07F7/0893

    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 WEAR PATTERNS
    69.
    发明申请
    EXTRACTING CARD DATA WITH WEAR PATTERNS 有权
    提取卡片数据与磨损模式

    公开(公告)号：US20150003667A1

    公开(公告)日：2015-01-01

    申请号：US14091093

    申请日：2013-11-26

    Applicant: GOOGLE INC.

    Inventor： Henry Allan Rowley ,  Sanjiv Kumar ,  Xiaohang Wang ,  Alessandro Bissacco ,  Jose Jeronimo Moreira Rodrigues ,  Kishore Ananda Papineni

    IPC: G06T3/00 ,  G06K9/62 ,  G06K9/18 ,  G06K9/66

    CPC classification number: G06K9/6269 ,  G06K9/00469 ,  G06K9/00536 ,  G06K9/18 ,  G06K9/186 ,  G06K9/3233 ,  G06K9/3258 ,  G06K9/46 ,  G06K9/6202 ,  G06K9/6267 ,  G06K9/66 ,  G06K2009/4666 ,  G06K2209/01 ,  G06Q20/227 ,  G06Q20/34 ,  G06T3/0012 ,  G06T7/11 ,  G06T2207/20132 ,  G07F7/0893

    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应用程序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。

    Clustering geofence-based alerts for mobile devices
    70.
    发明授权
    Clustering geofence-based alerts for mobile devices 有权
    针对移动设备群集基于地理位置的警报

    公开(公告)号：US08798646B1

    公开(公告)日：2014-08-05

    申请号：US13950511

    申请日：2013-07-25

    Applicant: Google Inc.

    Inventor： Xiaohang Wang ,  Farhan Shamsi ,  Yakov Okshtein ,  David Singleton ,  Debra Lin Repenning ,  Lixin Zhang ,  Marcus Alexander Foster

    IPC: H04M11/00 ,  G08B1/08 ,  H04W4/02 ,  H04W64/00

    CPC classification number: H04W4/021 ,  G06F17/3087 ,  G08B1/08 ,  H04W4/12 ,  H04W64/003

    Abstract: A geofence management system obtains location data for points of interest. The geofence management system determines, at the option of the user, the location of a user mobile computing device relative to specific points of interest and alerts the user when the user nears the points of interest. The geofence management system, however, determines relationships among the identified points of interest, and associates or “clusters” the points of interest together based on the determined relationships. Rather than establishing separate geofences for multiple points of interest, and then alerting the user each time the user's mobile device enters each geofence boundary, the geofence management system establishes a single geofence boundary for the associated points of interest. When the user's mobile device enters the clustered geofence boundary, the geofence management system notifies the user device to alert the user of the entrance event. The user then receives the clustered, geofence-based alert.

    Abstract translation: 地理围栏管理系统获取兴趣点的位置数据。 地理围栏管理系统可以根据用户的选择确定用户移动计算设备相对于特定兴趣点的位置，并且在用户接近兴趣点时提醒用户。 然而，地理围栏管理系统根据所确定的关系确定所识别的兴趣点之间的关系，以及关联点或“聚集”兴趣点在一起。 而不是为多个兴趣点建立单独的地理围栏，然后每当用户的移动设备进入每个地理围栏边界时提醒用户，地理围栏管理系统为相关联的兴趣点建立单一的地理围栏边界。 当用户的移动设备进入群集地理围栏边界时，地理围栏管理系统通知用户设备提醒用户入口事件。 然后，用户接收基于地理位置的群集警报。

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