A new adaptive threshold technique for improved matching in SIFT
DC Field | Value | Language |
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dc.contributor.author | Pirzada, Syed Jahanzeb Hussain | - |
dc.contributor.author | Baig, Mirza waqar | - |
dc.contributor.author | Haq, Ehsan Ul | - |
dc.contributor.author | Shin, Hyunchul | - |
dc.date.accessioned | 2021-06-23T12:03:32Z | - |
dc.date.available | 2021-06-23T12:03:32Z | - |
dc.date.issued | 2011-08 | - |
dc.identifier.issn | 1548-3746 | - |
dc.identifier.issn | 1558-3899 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/39084 | - |
dc.description.abstract | Scale Invariant Feature Transform (SIFT) is widely used in vision systems for various applications such as object detection and face recognition. In SIFT, threshold is applied to determine local extrema (keypoint selection) and global extrema (keypoint refinement). Next, descriptor matching is performed with selected keypoints. This paper presents a new method of adaptive thresholding which improves keypoint selection in SIFT. The value of adaptive threshold depends upon the average regional intensity of an image. Experimental results show that our method is robust for matching the keypoints among the images with illumination differences. Our new adaptive threshold technique for keypoint selection reduces false matches and shows significantly improved performance in experimental results. © 2011 IEEE. | - |
dc.format.extent | 4 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE | - |
dc.title | A new adaptive threshold technique for improved matching in SIFT | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/MWSCAS.2011.6026528 | - |
dc.identifier.scopusid | 2-s2.0-80053627441 | - |
dc.identifier.bibliographicCitation | 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), pp 1 - 4 | - |
dc.citation.title | 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS) | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 4 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Adaptive threshold technique | - |
dc.subject.keywordPlus | Adaptive thresholding | - |
dc.subject.keywordPlus | Adaptive thresholds | - |
dc.subject.keywordPlus | Descriptors | - |
dc.subject.keywordPlus | False matches | - |
dc.subject.keywordPlus | Keypoints | - |
dc.subject.keywordPlus | Local extremum | - |
dc.subject.keywordPlus | Object Detection | - |
dc.subject.keywordPlus | Scale invariant feature transforms | - |
dc.subject.keywordPlus | Vision systems | - |
dc.subject.keywordPlus | Face recognition | - |
dc.subject.keywordPlus | Object recognition | - |
dc.subject.keywordPlus | Feature extraction | - |
dc.subject.keywordAuthor | Object Detection | - |
dc.subject.keywordAuthor | Keypoints | - |
dc.subject.keywordAuthor | Face recognition | - |
dc.subject.keywordAuthor | Object recognition | - |
dc.subject.keywordAuthor | Adaptive thresholds | - |
dc.subject.keywordAuthor | Local extremum | - |
dc.subject.keywordAuthor | Scale invariant feature transforms | - |
dc.subject.keywordAuthor | False matches | - |
dc.subject.keywordAuthor | Adaptive thresholding | - |
dc.subject.keywordAuthor | Feature extraction | - |
dc.subject.keywordAuthor | Descriptors | - |
dc.subject.keywordAuthor | Vision systems | - |
dc.subject.keywordAuthor | Adaptive threshold technique | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/6026528 | - |
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