Pruning and Matching Scheme for Rotation Invariant Leaf Image Retrieval
DC Field | Value | Language |
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dc.contributor.author | Tak, Yoon-Sik | - |
dc.contributor.author | Hwang, Eenjun | - |
dc.date.accessioned | 2021-09-09T01:24:25Z | - |
dc.date.available | 2021-09-09T01:24:25Z | - |
dc.date.created | 2021-06-10 | - |
dc.date.issued | 2008-12-25 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/122198 | - |
dc.description.abstract | For efficient content-based image retrieval, diverse visual features such as color, texture, and shape have been widely used. In the case of leaf images, further improvement can be achieved based on the following observations. Most plants have unique shape of leaves that consist of one or more blades. Hence, blade-based matching can be more efficient than whole shape-based matching since the number and shape of blades are very effective to filtering out dissimilar leaves. Guaranteeing rotational invariance is critical for matching accuracy. In this paper, we propose a new shape representation, indexing and matching scheme for leaf image retrieval. For leaf shape representation, we generated a distance curve that is a sequence of distances between the leaf's center and all the contour points. For matching, we developed a blade-based matching algorithm called rotation invariant - partial dynamic time warping (RI-PDTW). To speed up the matching, we suggest two additional techniques: i) priority queue-based pruning of unnecessary blade sequences for rotational invariance, and ii) lower bound-based pruning of unnecessary partial dynamic time warping (PDTW) calculations. We implemented a prototype system on the GEMINI framework [1][2]. Using experimental results, we showed that our scheme achieves excellent performance compared to competitive schemes. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | KSII-KOR SOC INTERNET INFORMATION | - |
dc.title | Pruning and Matching Scheme for Rotation Invariant Leaf Image Retrieval | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Hwang, Eenjun | - |
dc.identifier.doi | 10.3837/tiis.2008.06.001 | - |
dc.identifier.scopusid | 2-s2.0-67650246623 | - |
dc.identifier.wosid | 000270933500001 | - |
dc.identifier.bibliographicCitation | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.2, no.6, pp.280 - 298 | - |
dc.relation.isPartOf | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS | - |
dc.citation.title | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS | - |
dc.citation.volume | 2 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 280 | - |
dc.citation.endPage | 298 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART001337108 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Shape-based image retrieval | - |
dc.subject.keywordAuthor | dynamic time warping | - |
dc.subject.keywordAuthor | sequence matching | - |
dc.subject.keywordAuthor | rotation invariance | - |
dc.subject.keywordAuthor | K-NN | - |
dc.subject.keywordAuthor | range search | - |
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