The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 31, 2024

Filed:

Mar. 28, 2019
Applicant:

Nielsen Consumer Llc, New York, NY (US);

Inventors:

Roberto Arroyo, Madrid, ES;

Javier Tovar Velasco, Valladolid, ES;

Francisco Javier Delgado Del Hoyo, Valladolid, ES;

Diego González Serrador, Valladolid, ES;

Emilio Almazán, Madrid, ES;

Antonio Hurtado, Valladolid, ES;

Assignee:

Nielsen Consumer LLC, Chicago, IL (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 30/413 (2022.01); G06N 3/08 (2023.01); G06V 10/25 (2022.01); G06V 10/82 (2022.01); G06V 20/62 (2022.01); G06V 30/414 (2022.01); G06V 30/416 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06V 10/25 (2022.01); G06V 10/82 (2022.01); G06V 20/62 (2022.01); G06V 30/413 (2022.01); G06V 30/414 (2022.01); G06V 30/416 (2022.01);
Abstract

Methods, apparatus, systems and articles of manufacture are disclosed to analyze characteristics of text of interest using a computing system. An example apparatus includes a text detector to provide text data from a first image, the first image including a first text region of interest and a second text region not of interest, a color-coding generator to generate a plurality of color-coded text-map images, the plurality of color-coded text-map images including color-coded segments with different colors, the color-coded segments corresponding to different text characteristics, and a convolutional neural network (CNN) to determine a first location in the first image as more likely to be the first text region of interest than a second location in the first image corresponding to the second text region that is not of interest based on performing a CNN analysis on the first image and the plurality of color-coded text-map images.


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