公开(公告)号：US08811656B2

公开(公告)日：2014-08-19

申请号：US14019670

申请日：2013-09-06

Applicant: Google Inc.

Inventor： Shlomo Urbach ,  Tal Yadid ,  Yuval Netzer ,  Andrea Frome ,  Noam Ben-Haim

IPC: G06K9/00

CPC classification number: G06K9/723 ,  G06F17/241 ,  G06F17/2705 ,  G06F17/30241 ,  G06K9/00664 ,  G06K2209/01

Abstract: Establishments are identified in geo-tagged images. According to one aspect, text regions are located in a geo-tagged image and text strings in the text regions are recognized using Optical Character Recognition (OCR) techniques. Text phrases are extracted from information associated with establishments known to be near the geographic location specified in the geo-tag of the image. The text strings recognized in the image are compared with the phrases for the establishments for approximate matches, and an establishment is selected as the establishment in the image based on the approximate matches. According to another aspect, text strings recognized in a collection of geo-tagged images are compared with phrases for establishments in the geographic area identified by the geo-tags to generate scores for image-establishment pairs. Establishments in each of the large collection of images as well as representative images showing each establishment are identified using the scores.

Abstract translation: 在地理标签图像中标识企业。 根据一个方面，文本区域位于地理标记的图像中，并且使用光学字符识别（OCR）技术识别文本区域中的文本串。 从与已知在图像的地理标签中指定的地理位置附近的企业相关联的信息中提取文本短语。 将图像中识别的文本字符串与用于近似匹配的场所的短语进行比较，并且基于近似匹配来选择企业作为图像中的建立。 根据另一方面，将在地理标签图像的集合中识别的文本字符串与由地理标签识别的地理区域中的企业的短语进行比较，以生成图像建立对的分数。 使用分数来确定每个大图像集合中的各个场所以及显示每个机构的代表性图像。

公开(公告)号：US20130294690A1

公开(公告)日：2013-11-07

申请号：US13937118

申请日：2013-07-08

Applicant: Google Inc.

Inventor： Shlomo Urbach ,  Eyal Fink ,  Tal Yadid ,  Yuval Netzer

IPC: G06K9/46 ,  G06K9/62

CPC classification number: G06K9/469 ,  G06K9/00449 ,  G06K9/00483 ,  G06K9/46 ,  G06K9/62 ,  G06K9/6224

Abstract: Techniques for identifying documents sharing common underlying structures in a large collection of documents and processing the documents using the identified structures are disclosed. Images of the document collection are processed to detect occurrences of a predetermined set of image features that are common or similar among forms. The images are then indexed in an image index based on the detected image features. A graph of nodes is built. Nodes in the graph represent images and are connected to nodes representing similar document images by edges. Documents sharing common underlying structures are identified by gathering strongly inter-connected nodes in the graph. The identified documents are processed based at least in part on the resulting clusters.

Abstract translation: 公开了用于识别在大量文档集合中共享共同底层结构的文档和使用所识别的结构处理文档的技术。 处理文档集合的图像以检测形式之间共同或相似的预定图像特征集合的出现。 然后基于检测到的图像特征将图像索引到图像索引中。 构建节点图。 图中的节点表示图像，并通过边缘连接到表示类似文档图像的节点。 通过在图中收集强相互连接的节点来识别共享通用底层结构的文档。 至少部分地基于所得到的集群来处理所识别的文档。

公开(公告)号：US08744183B2

公开(公告)日：2014-06-03

申请号：US13937118

申请日：2013-07-08

Applicant: Google Inc.

Inventor： Shlomo Urbach ,  Eyal Fink ,  Tal Yadid ,  Yuval Netzer

IPC: G06K9/00

CPC classification number: G06K9/469 ,  G06K9/00449 ,  G06K9/00483 ,  G06K9/46 ,  G06K9/62 ,  G06K9/6224

Abstract: Techniques for identifying documents sharing common underlying structures in a large collection of documents and processing the documents using the identified structures are disclosed. Images of the document collection are processed to detect occurrences of a predetermined set of image features that are common or similar among forms. The images are then indexed in an image index based on the detected image features. A graph of nodes is built. Nodes in the graph represent images and are connected to nodes representing similar document images by edges. Documents sharing common underlying structures are identified by gathering strongly inter-connected nodes in the graph. The identified documents are processed based at least in part on the resulting clusters.

Abstract translation: 公开了用于识别在大量文档集合中共享共同底层结构的文档和使用所识别的结构处理文档的技术。 处理文档集合的图像以检测形式之间共同或相似的预定图像特征集合的出现。 然后基于检测到的图像特征将图像索引到图像索引中。 构建节点图。 图中的节点表示图像，并通过边缘连接到表示类似文档图像的节点。 通过在图中收集强相互连接的节点来识别共享通用底层结构的文档。 至少部分地基于所得到的集群来处理所识别的文档。

公开(公告)号：US20140003650A1

公开(公告)日：2014-01-02

申请号：US14019670

申请日：2013-09-06

Applicant: Google Inc.

Inventor： Shlomo Urbach ,  Tal Yadid ,  Yuval Netzer ,  Andrea Frome ,  Noam Ben-Haim

IPC: G06K9/72 ,  G06K9/00

CPC classification number: G06K9/723 ,  G06F17/241 ,  G06F17/2705 ,  G06F17/30241 ,  G06K9/00664 ,  G06K2209/01

Abstract: Establishments are identified in geo-tagged images. According to one aspect, text regions are located in a geo-tagged image and text strings in the text regions are recognized using Optical Character Recognition (OCR) techniques. Text phrases are extracted from information associated with establishments known to be near the geographic location specified in the geo-tag of the image. The text strings recognized in the image are compared with the phrases for the establishments for approximate matches, and an establishment is selected as the establishment in the image based on the approximate matches. According to another aspect, text strings recognized in a collection of geo-tagged images are compared with phrases for establishments in the geographic area identified by the geo-tags to generate scores for image-establishment pairs. Establishments in each of the large collection of images as well as representative images showing each establishment are identified using the scores.

Abstract translation: 在地理标签图像中标识企业。 根据一个方面，文本区域位于地理标记的图像中，并且使用光学字符识别（OCR）技术识别文本区域中的文本串。 从与已知在图像的地理标签中指定的地理位置附近的企业相关联的信息中提取文本短语。 将图像中识别的文本字符串与用于近似匹配的场所的短语进行比较，并且基于近似匹配来选择企业作为图像中的建立。 根据另一方面，将在地理标签图像的集合中识别的文本字符串与由地理标签识别的地理区域中的企业的短语进行比较，以生成图像建立对的分数。 使用分数来确定每个大图像集合中的各个场所以及显示每个机构的代表性图像。