公开(公告)号：US09262682B2

公开(公告)日：2016-02-16

申请号：US14645410

申请日：2015-03-11

Applicant: GOOGLE INC.

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

IPC: G06K9/00 ,  G06K9/18 ,  G06K9/62 ,  G06K9/66 ,  G06T3/00 ,  G06Q20/22 ,  G06Q20/34 ,  G07F7/08 ,  G06K9/32

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.

公开(公告)号：US20160019530A1

公开(公告)日：2016-01-21

申请号：US14551991

申请日：2014-11-24

Applicant: GOOGLE INC.

Inventor： Xiaohang Wang ,  Glenn Berntson

IPC: G06Q20/34 ,  G06K9/18 ,  G06K9/00

CPC classification number: G06Q40/00 ,  G06K9/00442 ,  G06K9/18 ,  G06K9/3258 ,  G06K2209/01 ,  G06Q20/34 ,  G06Q20/351 ,  G06Q20/36 ,  H04N5/2257

Abstract: A user captures an image of a payment card via a user computing device camera. An optical character recognition system receives the payment card image from the user computing device. The system performs optical character recognition and visual object recognition algorithms on the payment card image to extract text and visual objects from the payment card image, which are used by the system to identify a payment card type. The system may categorize the payment card as a credit card or a non-credit card. In an example embodiment, the system determines that the payment card type is a credit card and transmits fee structure to the user. The user selects a second payment card for use in the transaction and the transaction is processed using financial account information associated with the second payment card.

Abstract translation: 用户通过用户计算设备相机捕获支付卡的图像。 光学字符识别系统从用户计算设备接收支付卡图像。 该系统在支付卡图像上执行光学字符识别和视觉对象识别算法，从支付卡图像中提取文本和视觉对象，系统用于识别支付卡类型。 系统可将支付卡分类为信用卡或非信用卡。 在示例实施例中，系统确定支付卡类型是信用卡，并向用户发送费用结构。 用户选择在交易中使用的第二支付卡，并且使用与第二支付卡相关联的金融账户信息来处理交易。

公开(公告)号：US09213907B2

公开(公告)日：2015-12-15

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: G06K9/62 ,  G06K9/18 ,  G06K9/66 ,  G06T3/00 ,  G06K9/00 ,  G06Q20/22 ,  G06Q20/34 ,  G07F7/08 ,  G06K9/32

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。

公开(公告)号：US20150264527A1

公开(公告)日：2015-09-17

申请号：US14727795

申请日：2015-06-01

Applicant: GOOGLE INC.

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

IPC: H04W4/02 ,  H04W4/12

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.

公开(公告)号：US09070183B2

公开(公告)日：2015-06-30

申请号：US14059108

申请日：2013-10-21

Applicant: GOOGLE INC.

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

IPC: G06K9/62 ,  G06T3/00 ,  G06K9/18 ,  G06K9/66 ,  G06K9/00 ,  G06Q20/22 ,  G06Q20/34 ,  G07F7/08 ,  G06K9/32

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。

公开(公告)号：US08995741B2

公开(公告)日：2015-03-31

申请号：US14461001

申请日：2014-08-15

Applicant: Google Inc.

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

IPC: G06K9/00 ,  G06K9/18

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。

公开(公告)号：US20150006360A1

公开(公告)日：2015-01-01

申请号：US14026738

申请日：2013-09-13

Applicant: GOOGLE INC.

Inventor： Sanjiv Kumar ,  Henry Allan Rowley ,  Xiaohang Wang ,  Yakov Okshtein ,  Farhan Shamsi ,  Alessandro Bissacco

IPC: G06Q20/32

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。

公开(公告)号：US20150003733A1

公开(公告)日：2015-01-01

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: G06K9/32

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。

公开(公告)号：US20150003732A1

公开(公告)日：2015-01-01

申请号：US14059108

申请日：2013-10-21

Applicant: GOOGLE INC.

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

IPC: G06K9/18

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。

公开(公告)号：US08903136B1

公开(公告)日：2014-12-02

申请号：US14133232

申请日：2013-12-18

Applicant: Google Inc.

Inventor： Xiaohang Wang ,  Alessandro Bissacco ,  Glen Berntson ,  Marria Nazif ,  Justin Scheiner ,  Sam Shih ,  Mark Leslie Snyder ,  Daniel Talavera

IPC: G06K9/00 ,  G06K9/18

CPC classification number: G06K9/00463 ,  G06K9/00979 ,  G06K9/036 ,  G06K9/18 ,  G06K9/4647 ,  G06K2209/01

Abstract: The technology of the present disclosure includes computer-implemented methods, computer program products, and systems to filter images before transmitting to a system for optical character recognition (“OCR”). A user computing device obtains a first image of the card from the digital scan of a physical card and analyzes features of the first image, the analysis being sufficient to determine if the first image is likely to be usable by an OCR algorithm. If the user computing device determines that the first image is likely to be usable, then the first image is transmitted to an OCR system associated with the OCR algorithm. Upon a determination that the first image is unlikely to be usable, a second image of the card from the digital scan of the physical card is analyzed. The optical character recognition system performs an optical character recognition algorithm on the filtered card.

Abstract translation: 本公开的技术包括计算机实现的方法，计算机程序产品和在发送到用于光学字符识别的系统（“OCR”）之前过滤图像的系统。 用户计算设备从物理卡的数字扫描中获取卡的第一图像并分析第一图像的特征，该分析足以确定第一图像是否可能被OCR算法可用。 如果用户计算设备确定第一图像可能是可用的，则将第一图像发送到与OCR算法相关联的OCR系统。 在确定第一图像不可能使用时，分析来自物理卡的数字扫描的卡的第二图像。 光学字符识别系统在滤波卡上执行光学字符识别算法。