Bayesian Approach to Photo Time-Stamp Recognition
Time-stamps and URLs overlaid artificially on images add useful meta information which can be used for automatic indexing of images and videos. In this paper, we propose a method based on an attention-based model of visual saliency to extract overlaid text and time-stamps that are rendered on images...
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| creator | Shahab, A. Shafait, F. Dengel, A. |
| description | Time-stamps and URLs overlaid artificially on images add useful meta information which can be used for automatic indexing of images and videos. In this paper, we propose a method based on an attention-based model of visual saliency to extract overlaid text and time-stamps that are rendered on images. Our model of visual saliency is based on a Bayesian framework and works very well for the task of time-stamp detection and segmentation as is evident by overall object recall of 80% and precision of 70%. Our method produces a clean text segmented binarized image, which can be used for recognition directly by an OCR system. Furthermore, our technique is robust against variation of font styles and color of time-stamp and overlaid text. |
| doi_str_mv | 10.1109/ICDAR.2011.210 |
| format | Conference Proceeding |
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Furthermore, our technique is robust against variation of font styles and color of time-stamp and overlaid text.</description><subject>Bayesian methods</subject><subject>Bayesian model for text detection</subject><subject>Image color analysis</subject><subject>Image recognition</subject><subject>Image segmentation</subject><subject>Optical character recognition software</subject><subject>overlaid text detection/recognition</subject><subject>photo time-stamp detection/recognition</subject><subject>Text recognition</subject><subject>visual saliency</subject><subject>Visualization</subject><issn>1520-5363</issn><issn>2379-2140</issn><isbn>1457713500</isbn><isbn>9781457713507</isbn><isbn>9780769545202</isbn><isbn>0769545203</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjMlOwzAURc0kEUq2bNjkBxz8PL9laBkqVQKVsq4c16ZGZFCSTf-eSHAX52yOLiF3wEoAhg_r5aralpwBlBzYGcnRWGY0Kqk44-ck48Ig5SDZBbkBqYwBoRi7JBnMAVVCi2uSj-M3m6c1goKMwKM7hTG5tqj6fuicPxZTV7wfu5m71AT6MbmmL7bBd19tmlLX3pKr6H7GkP97QT6fn3bLV7p5e1kvqw1NYNREjbYoZKwtcMSo0NZQx4AeZQCvuKmlh4M3XDsDzkYnXW0NesujYwclUSzI_d9vCiHs-yE1bjjtNdNKait-AcRYR4Q</recordid><startdate>201109</startdate><enddate>201109</enddate><creator>Shahab, A.</creator><creator>Shafait, F.</creator><creator>Dengel, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201109</creationdate><title>Bayesian Approach to Photo Time-Stamp Recognition</title><author>Shahab, A. ; Shafait, F. ; Dengel, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-768934fb81299f598b1bfe9c94e1c527b4c1dc726a71a8fa4ab879c82fa0d5493</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Bayesian methods</topic><topic>Bayesian model for text detection</topic><topic>Image color analysis</topic><topic>Image recognition</topic><topic>Image segmentation</topic><topic>Optical character recognition software</topic><topic>overlaid text detection/recognition</topic><topic>photo time-stamp detection/recognition</topic><topic>Text recognition</topic><topic>visual saliency</topic><topic>Visualization</topic><toplevel>online_resources</toplevel><creatorcontrib>Shahab, A.</creatorcontrib><creatorcontrib>Shafait, F.</creatorcontrib><creatorcontrib>Dengel, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shahab, A.</au><au>Shafait, F.</au><au>Dengel, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Bayesian Approach to Photo Time-Stamp Recognition</atitle><btitle>2011 International Conference on Document Analysis and Recognition</btitle><stitle>icdar</stitle><date>2011-09</date><risdate>2011</risdate><spage>1039</spage><epage>1043</epage><pages>1039-1043</pages><issn>1520-5363</issn><eissn>2379-2140</eissn><isbn>1457713500</isbn><isbn>9781457713507</isbn><eisbn>9780769545202</eisbn><eisbn>0769545203</eisbn><abstract>Time-stamps and URLs overlaid artificially on images add useful meta information which can be used for automatic indexing of images and videos. 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| ispartof | 2011 International Conference on Document Analysis and Recognition, 2011, p.1039-1043 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Bayesian methods Bayesian model for text detection Image color analysis Image recognition Image segmentation Optical character recognition software overlaid text detection/recognition photo time-stamp detection/recognition Text recognition visual saliency Visualization |
| title | Bayesian Approach to Photo Time-Stamp Recognition |
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