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Cited 8 time in webofscience Cited 10 time in scopus
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Max-min hand cropping method for robust hand region extraction in the image-based hand gesture recognition

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dc.contributor.authorJeong, Jinwoo-
dc.contributor.authorJang, Yoonhee-
dc.date.accessioned2024-09-26T14:01:57Z-
dc.date.available2024-09-26T14:01:57Z-
dc.date.issued2015-04-
dc.identifier.issn1432-7643-
dc.identifier.issn1433-7479-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/25385-
dc.description.abstractThere have been many developments and applications based on hand posture recognition to make human-computer interaction/interfaces more convenient and effective. And, many of these applications are based on the image-processing technique since it can guarantee more information and more flexibility for processing. To develop a hand posture recognition system, the proper extraction of pure hand region is a very important step since it is much related with the final performance and recognition rate. But, by the noisy data due to the illumination, image resolution, and non-uniform distribution of skin colors which could be easily found in real environments, it is not easy to extract the pure hand region exactly. In this research, a simple and effective algorithm for hand cropping, named as max-min hand cropping, is proposed and compared with some of the previous research. Finally, the effectiveness of the proposed method is verified with 152 different hand images from 8 persons and 19 hand postures.-
dc.format.extent4-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-
dc.titleMax-min hand cropping method for robust hand region extraction in the image-based hand gesture recognition-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/s00500-014-1391-9-
dc.identifier.scopusid2-s2.0-84925290846-
dc.identifier.wosid000351408300002-
dc.identifier.bibliographicCitationSOFT COMPUTING, v.19, no.4, pp 815 - 818-
dc.citation.titleSOFT COMPUTING-
dc.citation.volume19-
dc.citation.number4-
dc.citation.startPage815-
dc.citation.endPage818-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.subject.keywordAuthorMax-min hand cropping-
dc.subject.keywordAuthorHand region extraction-
dc.subject.keywordAuthorHand posture recognition-
dc.subject.keywordAuthorHuman-computer interaction-
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