US 10,372,981 B1Granted

Fast identification of text intensive pages from photographs

AssigneeEvernote Corporation

InventorsAlexander Pashintsev, Boris Gorbatov, Eugene Livshitz, Vitaly Glazkov

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Abstract

Determining if a document is a text page includes partitioning the document into a plurality of cells, scaling each of the cells to a standardized number of pixels to provide a corresponding snippet for each of the cells, using a classifier to examine the snippets to determine which of the cells are classified as text and which of the cells are not classified as text, determining a volume of text for the document based on a total amount of text in the document corresponding to a sum of an amount of text in each of the cells classified as text, and determining that the document is a text page in response to the total amount exceeding a pre-determined threshold. In response to the total amount being less than the pre-determined threshold, cells not classified as text may be examined further. The classifier may be provided by training a neural net.

Claims21

Dependent claims

A method of determining if a document is a text page, comprising:

partitioning the document into a first plurality of cells;
scaling each respective cell of the first plurality of cells to a standardized number of pixels to provide a first set of snippets, wherein the first set of snippets correspond to the first plurality of cells;
using a classifier to examine the first set of snippets to determine which of the first plurality of cells are classified as text and which of the cells are not classified as text;
determining a volume of text for the document based on a determined total amount of text in the document corresponding to a sum of an amount of text in each of the first plurality of cells classified as text;
determining whether the determined total amount of text in the document meets a pre-determined threshold;
in response to determining that the determined total amount of text in the document does not meet the pre-determined threshold and that criteria for a next partition level are met, for respective cells that are not classified as text:
a) applying further partitioning to the respective cells that are not classified as text to generate a respective further plurality of cells;
b) scaling each of the further partitioned cells to provide a respective further set of snippets that correspond to the further partitioned cells;
c) using the classifier to examine the respective further set of snippets to determine which of the respective further partitioned cells are classified as text and which of the respective further partitioned cells are not classified as text;
d) augmenting the volume of text for the document based on an updated determined total amount of text in the document corresponding to a sum of the amount of text in each of the cells of the plurality of cells and the respective further partitioned cells classified as text;
in response to determining that the augmented volume of text fort the document does not meet the pre-determined threshold and that criteria for a next partition level are met, repeating a)-d);
and
determining that the document is a text page in response to the determined total amount of text in the document exceeding the pre-determined threshold.

10 more elements

A non-transitory computer readable medium containing software that determines if a document is a text page, the software comprising:

executable code that partitions the document into a first plurality of cells;
executable code that scales each respective cell of the first plurality of cells to a standardized number of pixels to provide a first set of snippets, wherein the first set of snippets correspond to the first plurality of cells;
executable code that uses a classifier to examine the first set of snippets to determine which of the first plurality of cells are classified as text and which of the cells are not classified as text;
executable code that determines a volume of text for the document based on a determined total amount of text in the document corresponding to a sum of an amount of text in each of the first plurality of cells classified as text;
executable code that determines whether the determined total amount of text in the document meets a pre-determined threshold;
executable code that, in response to determining that the determined total amount of text in the document does not meet the pre-determined threshold and that criteria for a next partition level are met, for respective cells that are not classified as text:
a) applies further partitioning to the respective cells that are not classified as text to generate a respective further plurality of cells;
b) scales each of the further partitioned cells to provide a respective further set of snippets that correspond to the further partitioned cells;
c) uses the classifier to examine the respective further set of snippets to determine which of the respective further partitioned cells are classified as text and which of the respective further partitioned cells are not classified as text;
d) augments the volume of text for the document based on an updated determined total amount of text in the document corresponding to a sum of the amount of text in each of the cells of the plurality of cells and the respective further partitioned cells classified as text
executable code that, in response to determining that the augmented volume of text fort the document does not meet the pre-determined threshold and that criteria for a next partition level are met, repeats a)-d);
and
executable code that determines that the document is a text page in response to the total amount exceeding a pre-determined threshold.

10 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/272,744Filed 22 Sep 2016 · continuation
Priority: 23 Sep 2015
Granted: 6 Aug 2019
Term ends: Not estimatedThe source records don’t support an estimate.

Classification6 codes

G06V 30/413
Analysis of document content: classification of content, e.g. text, photographs or tables
G06T 3/40
Geometric image transformations in the plane of the image: scaling of whole images or parts thereof, e.g. expanding or contracting
G06T 7/60
Image analysis: analysis of geometric attributes
G06V 30/414
Analysis of document content: extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text

Family

Application62/222,368Parent of this continuation · filed 23 Sep 2015
US 10,372,981 B1This patent

From the US filing history. Foreign family members aren’t listed.

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