Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/61584
DC Field | Value | Language |
---|---|---|
dc.contributor | 資科系 | en_US |
dc.creator | 沈錳坤 | zh_TW |
dc.creator | Shan,Man-Kwan ; Wei,Ling-Yin | en_US |
dc.date | 2010.08 | en_US |
dc.date.accessioned | 2013-11-11T08:28:10Z | - |
dc.date.available | 2013-11-11T08:28:10Z | - |
dc.date.issued | 2013-11-11T08:28:10Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/61584 | - |
dc.description.abstract | Image mining is an important task to discover interesting and meaningful patterns form large image databases. In this paper, we introduce the spatial co-orientation patterns in image databases. Spatial co-orientation patterns refer to objects that frequently occur with the same spatial orientation, e.g. left, right, below, etc. among images. For example, an object P is frequently left to an object Q among images. We utilize the data structure, 2D string, to represent the spatial orientation of objects in an image. Two approaches, Apriori-based and pattern-growth approaches, are proposed for mining co-orientation patterns. An experimental evaluation with synthetic datasets shows the advantage and disadvantage between these two algorithms. | en_US |
dc.format.extent | 1187152 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.relation | Expert Systems with Applications: An International Journal, 37(8) , 5795-5802 | en_US |
dc.subject | Spatial co-orientation patterns; 2D string; Iconic images; Spatial mining | en_US |
dc.title | Algorithms for Discovery of Spatial Co-orientation Patterns from Images | en_US |
dc.type | article | en |
dc.identifier.doi | 10.1016/j.eswa.2010.02.028 | en_US |
dc.doi.uri | http://dx.doi.org/10.1016/j.eswa.2010.02.028 | en_US |
item.languageiso639-1 | en_US | - |
item.grantfulltext | restricted | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.openairetype | article | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
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57955802.pdf | 1.16 MB | Adobe PDF2 | View/Open |
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