| 講演名 | 2017-11-23 [Special Talk] SAR Image Segmentation Based Framework to Ship Detection Yang-Lang Chang(NTUT), Amare Anagaw Ayele(NTUT), Lena Chang(NTOU), Wei-Lin Chen(NTOU), Meng-Che Wu(NSPO), Chihyuan Chu(NTUT), |
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| 抄録(和) | Synthetic aperture radar (SAR) imagery has proven to be a promising data source for the surveillance of maritime activities, and its application for ship detection has been the focus of many research studies. In this work, we focus on a hierarchical image morphology based approach to perform detection of ship from the given SAR image. The framework does not require any prior knowledge about ships and background observation. The proposed framework has the following four main stages: 1) preprocessing (image alignment, remove unnecessary region and segmentation), 2) sea and land separation, 3) ship detection with feature extraction, and 4) combination of ship information from different segmented image (mark the collected information on the original image). Experiments on real SAR images with varying sea clutter backgrounds and multiple targets situation have been conducted. The effectiveness of the proposed framework is verified using Sentinel-1 data and Terra SAR-X images. The performance analysis confirms that the proposed framework works efficiently in various circumstances with high detection rate of 94.72% in average. |
| 抄録(英) | Synthetic aperture radar (SAR) imagery has proven to be a promising data source for the surveillance of maritime activities, and its application for ship detection has been the focus of many research studies. In this work, we focus on a hierarchical image morphology based approach to perform detection of ship from the given SAR image. The framework does not require any prior knowledge about ships and background observation. The proposed framework has the following four main stages: 1) preprocessing (image alignment, remove unnecessary region and segmentation), 2) sea and land separation, 3) ship detection with feature extraction, and 4) combination of ship information from different segmented image (mark the collected information on the original image). Experiments on real SAR images with varying sea clutter backgrounds and multiple targets situation have been conducted. The effectiveness of the proposed framework is verified using Sentinel-1 data and Terra SAR-X images. The performance analysis confirms that the proposed framework works efficiently in various circumstances with high detection rate of 94.72% in average. |
| キーワード(和) | feature extraction / ship detection / overlapped based segmentation / hierarchical image segmentation-based framework |
| キーワード(英) | feature extraction / ship detection / overlapped based segmentation / hierarchical image segmentation-based framework |
| 資料番号 | SANE2017-63 |
| 発行日 | 2017-11-16 (SANE) |
| 研究会情報 | |
| 研究会 | SANE |
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| 開催期間 | 2017/11/23(から2日開催) |
| 開催地（和） | マレーシア（ボルネオ島） |
| 開催地（英） | Malaysia (Borneo Island) |
| テーマ（和） | ICSANE2017 |
| テーマ（英） | ICSANE2017 |
| 委員長氏名（和） | 福島 荘之介(電子航法研) |
| 委員長氏名（英） | Sonosuke Fukushima(ENRI) |
| 副委員長氏名（和） | 森山 敏文(長崎大) / 灘井 章嗣(NICT) |
| 副委員長氏名（英） | Toshifumi Moriyama(Nagasaki Univ.) / Akitsugu Nadai(NICT) |
| 幹事氏名（和） | 小幡 康(三菱電機) / 毛塚 敦(電子航法研) |
| 幹事氏名（英） | Yasushi Obata(Mitsubishi Electric) / Atsushi Kezuka(ENRI) |
| 幹事補佐氏名（和） | 秋田 学(電通大) / 夏秋 嶺(東大) |
| 幹事補佐氏名（英） | Manabu Akita(Univ. of Electro-Comm.) / Ryo Natsuaki(Univ. of Tokyo) |
| 講演論文情報詳細 | |
| 申込み研究会 | Technical Committee on Space, Aeronautical and Navigational Electronics |
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| 本文の言語 | ENG |
| タイトル（和） | |
| サブタイトル（和） | |
| タイトル（英） | [Special Talk] SAR Image Segmentation Based Framework to Ship Detection |
| サブタイトル（和） | |
| キーワード(1)（和/英） | feature extraction / feature extraction |
| キーワード(2)（和/英） | ship detection / ship detection |
| キーワード(3)（和/英） | overlapped based segmentation / overlapped based segmentation |
| キーワード(4)（和/英） | hierarchical image segmentation-based framework / hierarchical image segmentation-based framework |
| 第 1 著者 氏名（和/英） | Yang-Lang Chang / Yang-Lang Chang |
| 第 1 著者 所属（和/英） | National Taipei University of Technology(略称：NTUT) National Taipei University of Technology(略称：NTUT) |
| 第 2 著者 氏名（和/英） | Amare Anagaw Ayele / Amare Anagaw Ayele |
| 第 2 著者 所属（和/英） | National Taipei University of Technology(略称：NTUT) National Taipei University of Technology(略称：NTUT) |
| 第 3 著者 氏名（和/英） | Lena Chang / Lena Chang |
| 第 3 著者 所属（和/英） | National Taiwan Ocean University(略称：NTOU) National Taiwan Ocean University(略称：NTOU) |
| 第 4 著者 氏名（和/英） | Wei-Lin Chen / Wei-Lin Chen |
| 第 4 著者 所属（和/英） | National Taiwan Ocean University(略称：NTOU) National Taiwan Ocean University(略称：NTOU) |
| 第 5 著者 氏名（和/英） | Meng-Che Wu / Meng-Che Wu |
| 第 5 著者 所属（和/英） | National Space Organization(略称：NSPO) National Space Organization(略称：NSPO) |
| 第 6 著者 氏名（和/英） | Chihyuan Chu / Chihyuan Chu |
| 第 6 著者 所属（和/英） | National Taipei University of Technology(略称：NTUT) National Taipei University of Technology(略称：NTUT) |
| 発表年月日 | 2017-11-23 |
| 資料番号 | SANE2017-63 |
| 巻番号（vol） | vol.117 |
| 号番号（no） | SANE-321 |
| ページ範囲 | pp.1-6(SANE), |
| ページ数 | 6 |
| 発行日 | 2017-11-16 (SANE) |