US 2019/0318163 A1 · FAST IDENTIFICATION OF TEXT INTENSIVE PAGES FROM PHOTOGRAPHS

Abstract

Methods and systems for training a neural network to distinguish between text documents and image documents are described. A corpus of text and image documents is obtained. A page of a text document is scanned by shifting a text window to a plurality of locations. In accordance with a determination that the text in the window at a respective location meets text line criteria, the text in the window is stored as a respective text snippet. A plurality of image windows are superimposed over at least one page of an image document. In accordance with a determination that the content of a respective image window meets image criteria, content of the image window is stored as a respective image snippet. The respective text snippet and the respective image snippet are provided to a classifier.

Claims20

Dependent claims

A method of training a neural network to distinguish between text documents and image documents, comprising:

obtaining a corpus of text and image documents;
for at least one text document of the corpus of text and image documents:
scanning at least one page of the at least one text document by shifting a text window to a plurality of locations on the at least one page of the at least one text document;
determining whether text in the window at a respective location of the plurality of locations meets text line criteria;
and
in accordance with a determination that the text in the window at the respective location of the plurality of locations meets text line criteria, storing the text in the window as a respective text snippet;
and
for at least one image document of the corpus of text and image documents:
superimposing a plurality of image windows over at least one page of the at least one image document;
determining whether the content of a respective image window meets image criteria;
and
in accordance with a determination that the content of the respective image window meets the image criteria, storing the content of the respective image window as a respective image snippet;
and
providing the respective text snippet and the respective image snippet to a classifier.

11 more elements

A computing device for training a neural network to distinguish between text documents and image documents, comprising:

one or more processors;
memory;
a display;
and
one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for:
obtaining a corpus of text and image documents;
for at least one text document of the corpus of text and image documents:
scanning at least one page of the at least one text document by shifting a text window to a plurality of locations on the at least one page of the at least one text document;
determining whether text in the window at a respective location of the plurality of locations meets text line criteria;
and
in accordance with a determination that the text in the window at the respective location of the plurality of locations meets text line criteria, storing the text in the window as a respective text snippet;
and
for at least one image document of the corpus of text and image documents:
superimposing a plurality of image windows over at least one page of the at least one image document;
determining whether the content of a respective image window meets image criteria;
and
in accordance with a determination that the content of the respective image window meets the image criteria, storing the content of the respective image window as a respective image snippet;
and
providing the respective text snippet and the respective image snippet to a classifier.

16 more elements

Dependencies are inferred from the claim text.

Fast identification of text intensive pages from photographs

Life of this patent

Fast identification of text intensive pages from photographs

Life of this patent

Abstract

Claims20