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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 1639 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 1631 | - |
dc.citation.title | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.citation.volume | 25 | - |
dc.contributor.author | Kim, Kwang In | - |
dc.contributor.author | Jung, Keechul | - |
dc.contributor.author | Kim, Jin Hyung | - |
dc.date.accessioned | 2023-12-22T11:07:57Z | - |
dc.date.available | 2023-12-22T11:07:57Z | - |
dc.date.created | 2019-02-25 | - |
dc.date.issued | 2003-12 | - |
dc.description.abstract | The current paper presents a novel texture-based method for detecting texts in images. A support vector machine (SVM) is used to analyze the textural properties of texts. No external texture feature extraction module is used; rather, the intensities of the raw pixels that make up the textural pattern are fed directly to the SVM, which works well even in high-dimensional spaces. Next, text regions are identified by applying a continuously adaptive mean shift algorithm (CAMSHIFT) to the results of the texture analysis. The combination of CAMSHIFT and SVMs produces both robust and efficient text detection, as time-consuming texture analyses for less relevant pixels are restricted, leaving only a small part of the input image to be texture-analyzed. | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.25, no.12, pp.1631 - 1639 | - |
dc.identifier.doi | 10.1109/TPAMI.2003.1251157 | - |
dc.identifier.issn | 0162-8828 | - |
dc.identifier.scopusid | 2-s2.0-0346750538 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/26218 | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/1251157 | - |
dc.identifier.wosid | 000186765000014 | - |
dc.language | 영어 | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.title | Texture-based approach for text detection in images using support vector machines and continuously adaptive mean shift algorithm | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic | - |
dc.relation.journalResearchArea | Computer Science; Engineering | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | text detection | - |
dc.subject.keywordAuthor | image indexing | - |
dc.subject.keywordAuthor | texture analysis | - |
dc.subject.keywordAuthor | support vector machine | - |
dc.subject.keywordAuthor | CAMSHIFT | - |
dc.subject.keywordPlus | FACE DETECTION | - |
dc.subject.keywordPlus | VIDEO | - |
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