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公开(公告)号：US20170039420A1
公开(公告)日：2017-02-09
申请号：US15297127
申请日：2016-10-18
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Jeff Huber , Farhan Shamsi , Yakov Okshtein , Sanjiv Kumar , Henry Allan Rowley , Marcus Quintana Mitchell , Debra Lin Repenning
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。
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公开(公告)号：US20160192152A1
公开(公告)日：2016-06-30
申请号：US15060205
申请日：2016-03-03
Applicant: GOOGLE INC.
Inventor： Michael James Taylor , Xiaohang Wang , Yakov Okshtein , Farhan Shamsi , Mohammad Hossain Sheikh Attar
CPC classification number: H04W4/027 , G01C21/3492 , G01C21/3626 , G01S1/68 , G01S19/39 , G01S19/42 , H04W4/023 , H04W64/006 , H04W84/12
Abstract: A location of a network user computing device is determined relative to a location of a point of interest. If the user device is determined to be stationary, the user device is monitored for movement, the movement resulting in re-determining the location of the user device relative to a location of the point of interest. If the user device is determined to be moving, the velocity of the user device is matched with a predetermined velocity, and a preliminary estimated time of arrival to the point of interest is determined based on the predetermined velocity matched to the user device. At a later time that is based on a function of the preliminary estimated time of arrival, an estimated time of arrival to the point of interest is verified based on the predetermined velocity matched to the user device.
Abstract translation: 网络用户计算设备的位置是相对于兴趣点的位置来确定的。 如果用户设备被确定为静止的，则监视用户设备的移动，该移动导致重新确定用户设备相对于该兴趣点的位置的位置。 如果确定用户设备正在移动，则用户设备的速度与预定速度相匹配，并且基于与用户设备匹配的预定速度来确定到达目标点的初步估计时间。 在基于初步预计到达时间的功能的较后时间，基于与用户设备匹配的预定速度来验证到达感兴趣点的估计时间。
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公开(公告)号：US20150371086A1
公开(公告)日：2015-12-24
申请号：US14837605
申请日：2015-08-27
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Jeff Huber , Farhan Shamsi , Yakov Okshtein , Sanjiv Kumar , Henry Allan Rowley , Marcus Quintana Mitchell , Debra Lin Repenning
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。
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公开(公告)号：US20150086069A1
公开(公告)日：2015-03-26
申请号：US14559888
申请日：2014-12-03
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Xiaohang Wang , Jose Moreira Rodrigues , Farhan Shamsi , Yakov Okshtein , Henry Allan Rowley , Marcus Quintana Mitchell , Zhifei Li
IPC: G06K9/00
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。
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公开(公告)号：US20150006362A1
公开(公告)日：2015-01-01
申请号：US14062655
申请日：2013-10-24
Applicant: GOOGLE INC.
Inventor： Marcus Quintana Mitchell , Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , Sanjiv Kumar , Henry Allan Rowley , Debra Lin Repenning
IPC: G06Q20/32
CPC classification number: G06K9/186 , G06K7/10 , G06K9/00469 , G06K9/03 , 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。
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Patent Agency Ranking
公开(公告)号：US08837833B1
公开(公告)日：2014-09-16
申请号：US14104901
申请日：2013-12-12
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
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。
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公开(公告)号：US08805125B1
公开(公告)日：2014-08-12
申请号：US14026479
申请日：2013-09-13
Applicant: Google Inc.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Xiaohang Wang , Yakov Okshtein , Farhan Shamsi , Alessandro Bissacco
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。
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公开(公告)号：US09872147B2
公开(公告)日：2018-01-16
申请号：US14572755
申请日：2014-12-16
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , David Singleton , Douglas Alexander Gresham , Alan Newberger , Lixin Zhang
CPC classification number: H04W4/027 , G01C21/00 , G01C21/3679 , H04L67/26 , H04W4/02 , H04W4/021 , H04W4/022 , H04W4/029 , H04W4/20 , H04W4/21
Abstract: Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.
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公开(公告)号：US20180014155A1
公开(公告)日：2018-01-11
申请号：US15710351
申请日：2017-09-20
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , David Singleton , Debra Lin Repenning , Lixin Zhang , Marcus Alexander Foster
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.
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公开(公告)号：US20170142550A1
公开(公告)日：2017-05-18
申请号：US15420676
申请日：2017-01-31
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , David Singleton , Debra Lin Repenning , Lixin Zhang , Marcus Alexander Foster
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.
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