Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Kim, Sungho | - |
dc.contributor.author | Sun, Sun-Gu | - |
dc.contributor.author | Kwon, Soon | - |
dc.contributor.author | Kim, Kyung-Tae | - |
dc.date.available | 2017-07-11T07:53:37Z | - |
dc.date.created | 2017-05-08 | - |
dc.date.issued | 2013 | - |
dc.identifier.isbn | 9780000000000 | - |
dc.identifier.issn | 0277-786X | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/3821 | - |
dc.description.abstract | This paper presents a novel coastal region detection method for infrared search and track. The coastal region detection is critical to home land security and ship defense. Detected coastal region information can be used to the design of target detector such as moving target detection and threshold setting. We can detect coastal regions robustly by combining the infrared image segmentation and sensor line-of-sight (LOS) information. The K-means-based image segmentation can provide initial region information and the sensor LOS information can predict the approximate horizon location in images. The evidence of coastal region is confirmed by contour extraction results. The experimental results on remote coasts and near coasts validate the robustness of the proposed coastal region detector. © 2013 SPIE. | - |
dc.publisher | SPIE | - |
dc.relation.ispartof | Automatic Target Recognition XXIII | - |
dc.title | Robust coastal region detection method using image segmentation and sensor LOS information for infrared search and track | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1117/12.2015720 | - |
dc.identifier.scopusid | 2-s2.0-84881176079 | - |
dc.identifier.bibliographicCitation | Automatic Target Recognition XXIII, v.8744 | - |
dc.citation.conferenceDate | 2013-04-29 | - |
dc.citation.conferencePlace | US | - |
dc.citation.conferencePlace | Baltimore, MD | - |
dc.citation.title | Automatic Target Recognition XXIII | - |
dc.citation.volume | 8744 | - |
dc.type.docType | Conference Paper | - |
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