WO2018097492A1 - Appareil et procédé d'analyse d'eau d'échantillon - Google Patents
Appareil et procédé d'analyse d'eau d'échantillon Download PDFInfo
- Publication number
- WO2018097492A1 WO2018097492A1 PCT/KR2017/011847 KR2017011847W WO2018097492A1 WO 2018097492 A1 WO2018097492 A1 WO 2018097492A1 KR 2017011847 W KR2017011847 W KR 2017011847W WO 2018097492 A1 WO2018097492 A1 WO 2018097492A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- moving
- information
- sample number
- zooplankton
- movement
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
- G06T7/0014—Biomedical image inspection using an image reference approach
- G06T7/0016—Biomedical image inspection using an image reference approach involving temporal comparison
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63C—LAUNCHING, HAULING-OUT, OR DRY-DOCKING OF VESSELS; LIFE-SAVING IN WATER; EQUIPMENT FOR DWELLING OR WORKING UNDER WATER; MEANS FOR SALVAGING OR SEARCHING FOR UNDERWATER OBJECTS
- B63C11/00—Equipment for dwelling or working underwater; Means for searching for underwater objects
- B63C11/02—Divers' equipment
- B63C11/30—Ballast
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
- G01N33/186—Water using one or more living organisms, e.g. a fish
- G01N33/1866—Water using one or more living organisms, e.g. a fish using microorganisms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Definitions
- the present invention relates to an apparatus and a method for analyzing sample water. More particularly, the present invention relates to an apparatus and method for analyzing sample water, which enables more accurate analysis of aquatic organisms to be applicable to a ballast water treatment system.
- ballast water or ballast water is installed on a ship to maintain balance when the ship is unloaded from the ship or the ship is loaded with very little cargo.
- ballast water treatment system satisfies the criteria, For example, suspended solids were also measured as living organisms, which caused problems with inaccuracy.
- the present invention has been made to solve the above problems, and in particular, the object of the present invention is to provide a sample number analysis apparatus and method that can more accurately determine aquatic life.
- model data comparing the continuously photographed images to obtain a moving area, generating movement information of the moving area, comparing the model data with moving information of the moving area, and moving the moving area. It is configured to determine the existence of living things in the area.
- the movement information may be composed of indexing information, a moving angle, and a moving distance.
- the location information of the present invention may be composed of a moving angle 213 and a moving distance 215, and may be configured with x and y coordinates as another embodiment.
- the moving area is obtained from the image photographed by the imaging unit 120, the information on which the same moving area moves between successive frames is compared with the model data to determine whether the living area is the animal (eg, zooplankton).
- the displayed size of the zooplankton 145 can be calculated based on the number of pixels in the horizontal and vertical directions of the moving areas 141a, 141b, and 141c and the actual size per pixel. For example, if the number of pixels in the area is 18 * 25 and the actual size per pixel is 2.5mm, the actual size is 45mm * 62.5 ⁇ , and the actual size is displayed on the display 140:
- the number of zooplankton above is configured to automatically display how many.
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Pathology (AREA)
- Immunology (AREA)
- Theoretical Computer Science (AREA)
- Ocean & Marine Engineering (AREA)
- Biochemistry (AREA)
- Mechanical Engineering (AREA)
- Analytical Chemistry (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Medical Informatics (AREA)
- Microbiology (AREA)
- Quality & Reliability (AREA)
- Radiology & Medical Imaging (AREA)
- Farming Of Fish And Shellfish (AREA)
Abstract
La présente invention concerne un appareil d'analyse d'eau d'échantillon, comprenant : une chambre dans laquelle de l'eau d'échantillon est reçue; une unité de capture d'image pour capturer des images de l'eau d'échantillon dans la chambre; et une unité de commande pour analyser les images capturées en continu par l'unité de capture d'image, l'unité de commande étant configurée pour utiliser des données d'apprentissage générées par l'intermédiaire d'un apprentissage automatique par réception en tant qu'entrée d'une pluralité d'images pour chaque type d'organisme, obtenir une zone de mouvement par comparaison des images capturées en continu, et déterminer les types d'organismes vivants dans la zone de mouvement par comparaison des données d'apprentissage et de la zone de mouvement, ce qui a pour effet de fournir un résultat d'analyse très précis par l'intermédiaire d'une reconnaissance d'image d'intelligence artificielle.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR10-2016-0157382 | 2016-11-24 | ||
KR1020160157382A KR101844928B1 (ko) | 2016-11-24 | 2016-11-24 | 샘플수 분석장치 및 방법 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2018097492A1 true WO2018097492A1 (fr) | 2018-05-31 |
Family
ID=61973363
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/KR2017/011847 WO2018097492A1 (fr) | 2016-11-24 | 2017-10-25 | Appareil et procédé d'analyse d'eau d'échantillon |
Country Status (2)
Country | Link |
---|---|
KR (1) | KR101844928B1 (fr) |
WO (1) | WO2018097492A1 (fr) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110487980A (zh) * | 2019-06-27 | 2019-11-22 | 江苏亚寰环保科技股份有限公司 | 一种基于人工智能与机器学习算法的水环境监测分析系统 |
CN110702869A (zh) * | 2019-11-01 | 2020-01-17 | 无锡中科水质环境技术有限公司 | 基于视频图像解析的鱼类应激回避行为水质监测方法 |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR102294417B1 (ko) * | 2019-11-04 | 2021-08-26 | 주식회사 테크로스 | 샘플수 분석장치 및 방법 |
KR102324418B1 (ko) * | 2020-05-11 | 2021-11-15 | 주식회사 테크로스 | 수중생물 측정장치 및 방법 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2002230555A (ja) * | 2001-02-01 | 2002-08-16 | Noa Syst:Kk | 動きを検知する検知装置及び方法 |
KR20080090734A (ko) * | 2007-04-05 | 2008-10-09 | (주)월드이엔지 | 영상처리를 이용한 선박 밸러스트 워터 검사 장치 및 그방법 |
KR20110050289A (ko) * | 2009-11-06 | 2011-05-13 | 주식회사 파나시아 | 밸러스트수 실시간 감시장치 및 이를 이용한 감시방법 |
KR20120100581A (ko) * | 2011-03-04 | 2012-09-12 | 주식회사 엔케이 | 선박용 밸러스트수의 모니터링 시스템 |
KR20160078955A (ko) * | 2013-10-28 | 2016-07-05 | 몰레큘라 디바이스 엘엘씨 | 현미경 이미지 내에서 각각의 세포를 분류 및 식별하는 방법 및 시스템 |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4674920B2 (ja) | 2009-06-15 | 2011-04-20 | 独立行政法人産業技術総合研究所 | 対象個数検出装置および対象個数検出方法 |
JP2016095259A (ja) | 2014-11-17 | 2016-05-26 | 横河電機株式会社 | プランクトン測定システムおよびプランクトン測定方法 |
-
2016
- 2016-11-24 KR KR1020160157382A patent/KR101844928B1/ko active IP Right Grant
-
2017
- 2017-10-25 WO PCT/KR2017/011847 patent/WO2018097492A1/fr active Application Filing
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2002230555A (ja) * | 2001-02-01 | 2002-08-16 | Noa Syst:Kk | 動きを検知する検知装置及び方法 |
KR20080090734A (ko) * | 2007-04-05 | 2008-10-09 | (주)월드이엔지 | 영상처리를 이용한 선박 밸러스트 워터 검사 장치 및 그방법 |
KR20110050289A (ko) * | 2009-11-06 | 2011-05-13 | 주식회사 파나시아 | 밸러스트수 실시간 감시장치 및 이를 이용한 감시방법 |
KR20120100581A (ko) * | 2011-03-04 | 2012-09-12 | 주식회사 엔케이 | 선박용 밸러스트수의 모니터링 시스템 |
KR20160078955A (ko) * | 2013-10-28 | 2016-07-05 | 몰레큘라 디바이스 엘엘씨 | 현미경 이미지 내에서 각각의 세포를 분류 및 식별하는 방법 및 시스템 |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110487980A (zh) * | 2019-06-27 | 2019-11-22 | 江苏亚寰环保科技股份有限公司 | 一种基于人工智能与机器学习算法的水环境监测分析系统 |
CN110702869A (zh) * | 2019-11-01 | 2020-01-17 | 无锡中科水质环境技术有限公司 | 基于视频图像解析的鱼类应激回避行为水质监测方法 |
Also Published As
Publication number | Publication date |
---|---|
KR101844928B1 (ko) | 2018-04-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2018097491A1 (fr) | Appareil et procédé d'analyse d'un échantillon d'eau | |
WO2018097492A1 (fr) | Appareil et procédé d'analyse d'eau d'échantillon | |
CN105488468B (zh) | 一种目标区域的定位方法和装置 | |
Faillettaz et al. | Imperfect automatic image classification successfully describes plankton distribution patterns | |
CN104077594B (zh) | 一种图像识别方法和装置 | |
KR101743270B1 (ko) | 다수의 플랑크톤이 응집 혹은 산재해 있는 현미경 영상에서 딥러닝을 이용하여 개개 플랑크톤을 분리 및 인식하는 방법 | |
KR100889997B1 (ko) | 영상처리를 이용한 선박 밸러스트 워터 검사 장치 및 그방법 | |
JP2007187575A (ja) | 水質監視装置および水質監視方法 | |
CN116503335B (zh) | 一种水生物监测系统、方法、装置和存储介质 | |
CN112200011A (zh) | 曝气池状态检测方法、系统、电子设备及存储介质 | |
CN114170549A (zh) | 一种基于深度学习的水面漂浮物检测方法 | |
CN113239854A (zh) | 一种基于深度学习的船舶身份识别方法及系统 | |
Beyan et al. | A filtering mechanism for normal fish trajectories | |
Chen et al. | Real-time learning-based monitoring system for water contamination | |
Skøien et al. | A computer vision approach for detection and quantification of feed particles in marine fish farms | |
Gal | Automatic obstacle detection for USV’s navigation using vision sensors | |
CN114155470A (zh) | 一种河道区域入侵检测方法、系统及存储介质 | |
CN108229281A (zh) | 神经网络的生成方法和人脸检测方法、装置及电子设备 | |
Abalos et al. | Fresh fish classification using hog feature extraction and svm | |
CN115376210B (zh) | 泳池防溺水的溺水行为识别方法、装置、设备及介质 | |
KR102294417B1 (ko) | 샘플수 분석장치 및 방법 | |
Chan et al. | Real-time Detection of Aquarium Fish Species Using YOLOv4-tiny on Raspberry Pi 4 | |
CN114005064A (zh) | 一种基于机器视觉技术的生物式水体污染预警方法及装置 | |
KR102105184B1 (ko) | 샘플수 분석장치 및 방법 | |
CN114782368A (zh) | 基于视觉检测融合多动态阈值的虾苗自动计数方法及系统 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 17872936 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 17872936 Country of ref document: EP Kind code of ref document: A1 |