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公开(公告)号：US20180089587A1
公开(公告)日：2018-03-29
申请号：US15676076
申请日：2017-08-14
Applicant: Google Inc.
Inventor： Ananda Theertha Suresh , Sanjiv Kumar , Hugh Brendan McMahan , Xinnan Yu
Abstract: The present disclosure provides systems and methods for communication efficient distributed mean estimation. In particular, aspects of the present disclosure can be implemented by a system in which a number of vectors reside on a number of different clients, and a centralized server device seeks to estimate the mean of such vectors. According to one aspect of the present disclosure, a client computing device can rotate a vector by a random rotation matrix and then subsequently perform probabilistic quantization on the rotated vector. According to another aspect of the present disclosure, subsequent to quantization but prior to transmission, the client computing can encode the quantized vector according to a variable length coding scheme (e.g., by computing variable length codes).
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公开(公告)号：US20170083797A1
公开(公告)日：2017-03-23
申请号：US15364222
申请日：2016-11-29
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Xiaohang Wang , Jose Jeronimo Moreira Rodrigues
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.
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公开(公告)号：US20160267345A1
公开(公告)日：2016-09-15
申请号：US15158520
申请日：2016-05-18
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.
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公开(公告)号：US09436707B2
公开(公告)日：2016-09-06
申请号：US14330195
申请日：2014-07-14
Applicant: Google Inc.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Ameesh Makadia
CPC classification number: G06F17/30274 , G06F17/30247 , G06K9/6215 , G06K9/6224 , G06K2209/27
Abstract: Methods, systems, and apparatus, including computer program products, for ranking search results for queries. The method includes calculating a visual similarity score for one or more pairs of images in a plurality of images based on visual features of images in each of the one or more pairs; building a graph of images by linking each of one or more images in the plurality of images to one or more nearest neighbor images based on the visual similarity scores; associating a respective score with each of one or more images in the graph based on data indicative of user behavior relative to the image as a search result for a query; and determining a new score for each of one or more images in the graph based on the respective score of the image, and the respective scores of one or more nearest neighbors to the image.
Abstract translation: 方法，系统和装置，包括计算机程序产品，用于对查询的搜索结果进行排名。 该方法包括基于一个或多个对中的每一个中的图像的视觉特征来计算多个图像中的一对或多对图像的视觉相似性分数; 通过基于所述视觉相似性得分将所述多个图像中的一个或多个图像的每一个链接到一个或多个最近邻图像来构建图像的图; 基于表示用户相对于图像的行为的数据作为查询的搜索结果，将各个分数与图中的一个或多个图像中的每一个相关联; 以及基于所述图像的相应分数以及所述图像的一个或多个最近邻居的各个分数来确定所述图中的一个或多个图像中的每一个的新分数。
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公开(公告)号：US09292740B2
公开(公告)日：2016-03-22
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
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.
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Patent Agency Ranking
公开(公告)号：US20150186740A1
公开(公告)日：2015-07-02
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: G06K9/18
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.
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公开(公告)号：US20150006361A1
公开(公告)日：2015-01-01
申请号：US14026781
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：US20150003666A1
公开(公告)日：2015-01-01
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: G06K9/18
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.
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公开(公告)号：US20150001300A1
公开(公告)日：2015-01-01
申请号：US14077780
申请日：2013-11-12
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Xiaohang Wang , Jose Moreira Rodrigues , Farhan Shamsi , Yakov Okshtein , Henry Allan Rowley , Marcus Quintana Mitchell , Zhifei Li
IPC: G06K7/10
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.
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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.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Xiaohang Wang , Jose Jeronimo Moreira Rodrigues
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。
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