US Patent Application 18354101. Efficiently Augmenting Images with Related Content simplified abstract

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Efficiently Augmenting Images with Related Content

Organization Name

Google LLC


Inventor(s)

Charles Yang of Fremont CA (US)

Louis Wang of San Francisco CA (US)

Charles J. Rosenberg of Cupertino CA (US)

Efficiently Augmenting Images with Related Content - A simplified explanation of the abstract

This abstract first appeared for US patent application 18354101 titled 'Efficiently Augmenting Images with Related Content

Simplified Explanation

- This patent application is about a system that provides content related to text depicted in images. - The system includes a data processing apparatus that can extract text from an image. - The extracted text is divided into multiple blocks and presented as selectable targets on a user interface at a certain zoom level. - When a user selects a block of text, the system detects the selection and presents portions of the text within that block as selectable targets at a higher zoom level. - If the user selects a portion of the text within the block, an action is initiated based on the content of the selected text.


Original Abstract Submitted

The subject matter of this specification generally relates to providing content related to text depicted in images. In one aspect, a system includes a data processing apparatus configured to extract text from an image. The extracted text is partitioned into multiple blocks. The multiple blocks are presented as respective first user-selectable targets on a user interface at a first zoom level. A user selection of a first block of the multiple blocks is detected. In response to detecting the user selection of the first block, portions of the extracted text in the first block are presented as respective second user-selectable targets on the user interface at a second zoom level greater than the first zoom level. In response to detecting a user selection of a portion of the extracted text within the first block, an action is initiated based on content of the user-selected text.

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