METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS
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...
Gespeichert in:
Hauptverfasser: | , , , , , |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | Arroyo, Roberto Tovar Velasco, Javier Almazán, Emilio Hurtado, Antonio Serrador, Diego González Delgado Del Hoyo, Francisco Javier |
description | 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. |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2022189190A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2022189190A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2022189190A13</originalsourceid><addsrcrecordid>eNqNjMEKglAQRd20iOofBloLaptcTr7xOaDviTOCrUTiBUGUYP9PLvqAVvfAOdxt9GhIK28E0BnAtsUOtRdQD4aUCgUEpUGhI8vegS-BnVJHoius0rBlxRq4QUvQCzsLDRYVO4ovKLSeOqyvwrKPNvfpuYTDb3fRsSQtqjjM7zEs83QLr_AZe8mSLEvPeZonmJ7-q77O7TYt</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS</title><source>esp@cenet</source><creator>Arroyo, Roberto ; Tovar Velasco, Javier ; Almazán, Emilio ; Hurtado, Antonio ; Serrador, Diego González ; Delgado Del Hoyo, Francisco Javier</creator><creatorcontrib>Arroyo, Roberto ; Tovar Velasco, Javier ; Almazán, Emilio ; Hurtado, Antonio ; Serrador, Diego González ; Delgado Del Hoyo, Francisco Javier</creatorcontrib><description>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.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; PHYSICS</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220616&DB=EPODOC&CC=US&NR=2022189190A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220616&DB=EPODOC&CC=US&NR=2022189190A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Arroyo, Roberto</creatorcontrib><creatorcontrib>Tovar Velasco, Javier</creatorcontrib><creatorcontrib>Almazán, Emilio</creatorcontrib><creatorcontrib>Hurtado, Antonio</creatorcontrib><creatorcontrib>Serrador, Diego González</creatorcontrib><creatorcontrib>Delgado Del Hoyo, Francisco Javier</creatorcontrib><title>METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS</title><description>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.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjMEKglAQRd20iOofBloLaptcTr7xOaDviTOCrUTiBUGUYP9PLvqAVvfAOdxt9GhIK28E0BnAtsUOtRdQD4aUCgUEpUGhI8vegS-BnVJHoius0rBlxRq4QUvQCzsLDRYVO4ovKLSeOqyvwrKPNvfpuYTDb3fRsSQtqjjM7zEs83QLr_AZe8mSLEvPeZonmJ7-q77O7TYt</recordid><startdate>20220616</startdate><enddate>20220616</enddate><creator>Arroyo, Roberto</creator><creator>Tovar Velasco, Javier</creator><creator>Almazán, Emilio</creator><creator>Hurtado, Antonio</creator><creator>Serrador, Diego González</creator><creator>Delgado Del Hoyo, Francisco Javier</creator><scope>EVB</scope></search><sort><creationdate>20220616</creationdate><title>METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS</title><author>Arroyo, Roberto ; Tovar Velasco, Javier ; Almazán, Emilio ; Hurtado, Antonio ; Serrador, Diego González ; Delgado Del Hoyo, Francisco Javier</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2022189190A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Arroyo, Roberto</creatorcontrib><creatorcontrib>Tovar Velasco, Javier</creatorcontrib><creatorcontrib>Almazán, Emilio</creatorcontrib><creatorcontrib>Hurtado, Antonio</creatorcontrib><creatorcontrib>Serrador, Diego González</creatorcontrib><creatorcontrib>Delgado Del Hoyo, Francisco Javier</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Arroyo, Roberto</au><au>Tovar Velasco, Javier</au><au>Almazán, Emilio</au><au>Hurtado, Antonio</au><au>Serrador, Diego González</au><au>Delgado Del Hoyo, Francisco Javier</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS</title><date>2022-06-16</date><risdate>2022</risdate><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.</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | eng |
recordid | cdi_epo_espacenet_US2022189190A1 |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING PHYSICS |
title | METHODS AND APPARATUS TO DETECT A TEXT REGION OF INTEREST IN A DIGITAL IMAGE USING MACHINE-BASED ANALYSIS |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T19%3A57%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Arroyo,%20Roberto&rft.date=2022-06-16&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2022189190A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |