WO2013053597A1 - Procédé et système de détection d'un pou sur un poisson - Google Patents

Procédé et système de détection d'un pou sur un poisson Download PDF

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Publication number
WO2013053597A1
WO2013053597A1 PCT/EP2012/068921 EP2012068921W WO2013053597A1 WO 2013053597 A1 WO2013053597 A1 WO 2013053597A1 EP 2012068921 W EP2012068921 W EP 2012068921W WO 2013053597 A1 WO2013053597 A1 WO 2013053597A1
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WO
WIPO (PCT)
Prior art keywords
image
louse
fish
sub
searching
Prior art date
Application number
PCT/EP2012/068921
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English (en)
Inventor
Baard RØSVIK
Original Assignee
Salvision As
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Salvision As filed Critical Salvision As
Publication of WO2013053597A1 publication Critical patent/WO2013053597A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K61/00—Culture of aquatic animals
    • A01K61/10—Culture of aquatic animals of fish
    • A01K61/13—Prevention or treatment of fish diseases
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K61/00—Culture of aquatic animals
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K61/00—Culture of aquatic animals
    • A01K61/90—Sorting, grading, counting or marking live aquatic animals, e.g. sex determination
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
    • Y02A40/81—Aquaculture, e.g. of fish

Definitions

  • the present invention relates to a method and system for detecting a louse on a fish.
  • the salmon louse has a life cycle of ten life cycle stages, where stages four to seven are the chalimus stages where the louse is attached to the salmon and eats from the salmon, and where stages eight to ten are the adult stages where the louse is mobile. In these last stages, it is also possible to differentiate between male and female lice (see for example http://en.wikipedia.org/wiki/Salmon_louse). There are other types of fish lice that have similar life cycles and similar appearance.
  • a fish farming facility such as a fish farming tank, fish farming cage etc
  • an image recorder film or individual images
  • the number of lice can be counted manually by viewing the image recordings.
  • the object of the invention is to provide a method and system for detecting the presence of a louse on a fish. Moreover, it is an object to count the number of lice if more than one louse is present. It is also an object of the invention to provide a method and system where it is possible to detect the stage in which each louse on the fish belongs to. It is also an important object of the invention to provide a method and system which is fast and efficient.
  • the present invention relates to a method for detecting a louse on a fish, comprising the steps of:
  • the storing of information comprises storing information about the position of the sub-image in the image.
  • the predetermined louse-shaped object comprises a first, substantially circular object, a second, substantially circular object connected to the first object and a third, substantially rectangular object connected to the second object.
  • the louse-shaped object comprises an image of a louse.
  • the image of the louse is retrieved from a database of louse images.
  • the step of storing information about the sub-image further comprises:
  • the step of storing information about the sub-image further comprises:
  • the method further comprises the step of:
  • the method further comprises the step of performing an image differentiating algorithm before the step of searching for the predetermined louse pattern.
  • the method further comprises the step of increasing a lice counter for each louse found in the image.
  • the method is further comprising the step of computing the average number of lice per fish.
  • the invention also relates to a system for detecting a louse on a fish, comprising:
  • central processing unit connected to the image recorder and to the computer memory, where the central processing unit is configured to perform the method according to the above.
  • the present invention also relates to a method for detecting a louse on a fish, comprising the steps of:
  • the method is further comprising:
  • Fig. 1 illustrates the system for detecting a louse on a fish
  • Fig. 2 illustrates the steps of a method for detecting a louse on a fish
  • Fig. 3 illustrates a predetermined louse-shaped object
  • Fig. 4 illustrates a screen image of the system running on a computer device, where it is shown that a louse is detected on the fish;
  • Fig. 5 shows an image as received from the image recorder, where a louse is indicated by a dashed circle
  • Fig. 6a shows the image in fig. 5 after the color filtration process
  • Fig. 6b shows an enlarged view of the louse found in fig. 6a;
  • Fig. 7a shows the image in fig. 5 and fig. 6a after a pixel recoding process
  • Fig. 7b shows an enlarged view of the louse found in fig. 7a
  • fig. 1 illustrating a system 1 for detecting a louse on a fish.
  • the system 1 comprises an image recorder 2 for recording an image of the fish.
  • the image recorder may record still images (photos) or film, in the present embodiment the image recorder records a still image of the side of the fish.
  • the system may comprise several image recorders, for example one image of each side surface of the fish.
  • image recorders may be provided to record a top image of the fish, a bottom image of the fish etc.
  • the image recorder could record images of only parts of the fish instead of images of the entire fish, i.e. in order to analyze one fish, the image recorder must record several images.
  • the image recorder is a digital camera.
  • the image recorder 2 is connected to a computer device 3, comprising a central processing unit or CPU 4 and a computer memory 5.
  • the computer device 3 can any type of computer device and is considered known for a skilled person.
  • the computer device 3 is further connected to a user interface, such as a screen, a keyboard, a mouse etc.
  • a user interface such as a screen, a keyboard, a mouse etc.
  • the system 1 in one unit, where the unit comprises the image recorder, the computer memory and the CPU in one unit, and where the output from such a unit is a number display showing the average number of lice per fish.
  • the system 1 can be provided with an entrance for the fish and an exit for the fish, in order to ensure that only one fish passes the image recorder simultaneously.
  • sensors can be provided in order to be able to record the image of the fish when the fish is in the correct position in front of the camera.
  • the image of the fish may be provided when the fish is fetched from water or when the fish is submerged in water.
  • a method for detecting a louse on a fish is implemented as a computer program running on the CPU 4.
  • the central processing unit 4 of the computer device 3 is configured to perform the method described below.
  • a first step 10 the computer device 3 is receiving an image of a fish from the image recorder 2.
  • the image is provided in an electronic file format, typically a JPG format, a PNG format or another suitable format.
  • An example of such an image is shown in fig. 5, where a dashed circle is indicating the position of a louse.
  • the image in fig. 5 has a size of ca 2.6 MB.
  • the computer device 3 is manipulating the image by performing the following steps:
  • the computer device 3 is searching for pixels having colors within a background color interval and setting those pixels to a default pixel value.
  • the background color interval is a predetermined interval of colors which are considered to define the background of the image. Hence, if no fish is present, the image will contain only colors within the background color interval.
  • color here is used both for color images, where the pixel may have a value for each of the colors red, green and blue, alternatively a value for each of the colors cyan, magenta, yellow and black.
  • color may also represent shades of grey in a black and white image.
  • the default pixel value could typically be a non-color value, for example -1 or pure black or pure white.
  • the image recorder may be directed towards a surface having a color different from the color of the fish and the color of the fish surface.
  • step 14 the computer device 3 is searching for pixels having colors within a fish surface color interval and setting those pixels to the default pixel value.
  • the fish surface color interval is a predetermined interval of colors which are considered to define the fish surface of the image.
  • step 12 and 14 may be performed simultaneously.
  • the method is iterating through the pixels of the image only once while searching for pixels having colors within a background color interval and while searching for pixels having colors within a fish surface color interval.
  • Fig. 6a is showing the image in fig. 5 after step 12 and 14 has been performed.
  • fig. 6b An enlarged view of the louse as apparent from fig. 6a is shown in fig. 6b.
  • searching steps 12 and 14 will have reduced the amount of
  • the image in fig. 5 has a size of ca 9 kB, i.e. the information in this image has been reduced considerably.
  • step 16 the computer device 3 is searching for a predetermined louse-shaped object in those parts of the image having a pixel value different from the default value.
  • the predetermined louse-shaped object may be an object or specification making it possible to determine whether a louse actually is present in those parts of the image having a pixel value different from the default value or not.
  • the predetermined louse-shaped object 30 may comprise a predetermined shape as in fig. 3, comprising a first, substantially circular object 31 , a second, substantially circular object 32 connected to the first object 31 and a third, substantially rectangular object 33 connected to the second object 32.
  • a threshold value may be used to determine how close to the image these objects must be in order to define a louse.
  • One additional criterion may be that these objects may be partially overlapping.
  • an additional criterion may be that these objects are oriented along a line I-I.
  • the predetermined louse-shaped object comprises an image of a louse.
  • an image recognition algorithm is performed for comparing the image of a louse and those parts of the image having a pixel value different from the default value. It is possible to provide the system with a database of louse images and retrieve the image of the louse from the database of louse images.
  • the database could comprise several images and compare those parts of the image having a pixel value different from the default value with one or several of the images in the database.
  • louse was found by searching for a predetermined louse-shaped object in the form of a predetermined shape, as the one shown and described above with respect to fig. 3. Yet another test was performed, and the louse was also found by comparing fig. 6a with images of lice.
  • step 18 the computer device 3 is determining if the predetermined louse-shaped object is found in the image. Hence the computer device 3 is determining whether or not one or several lice are present in the image.
  • the computer device 3 is performing the steps of providing a sub-image of the image, where the sub-image is containing the area of the image in which the predetermined louse-shaped object is found (step 20). Moreover, the computer device 3 is storing information about the sub-image, where the storing of information comprises storing information about the position of the sub-image in the image (step 22). Then, in step 24, the method ends.
  • the sub-image is shown by a dashed square in fig. 6b, where also the length L and the width W are indicated. If no predetermined louse-shaped object is found, the method starts over again by receiving a new image in step 10. Alternatively, for example if there are no further images, the method ends.
  • the step 22 of storing information about the sub-image may further comprise storing the width and length of the sub-image.
  • the computer device 3 may determine a life cycle stage of the louse based on the width and length of the sub- image.
  • the step 22 of storing information about the sub-image may further comprise storing the contour of the louse in the sub-image.
  • the contour of the louse may be stored in the database and may be used in the searching for a predetermined louse- shaped object, step 16 in other images.
  • the received image of the fish may be taken under controlled light conditions.
  • the method is assumed to be more reliable with respect to the searching for pixels having colors within a background color interval, the searching for pixels having colors within a fish surface color interval and the searching for a predetermined louse-shaped object in those parts of the image having a pixel value different from the default value.
  • the method further may comprise the step of performing an image differentiating algorithm after the searching steps 12 and 14, but before step 16 of searching for the predetermined louse pattern.
  • the differentiating algorithm may be an algorithm where pixel values are recoded, for example to a binary image, for faster shape recognition.
  • the image differentiating algorithm can be performed in several iterations.
  • Fig. 7a shows the image of fig. 6a where such an image differentiating algorithm has been performed.
  • all pixels in the image are either black or white.
  • An enlarged view of the louse as apparent from fig. 7a is shown in fig. 7b.
  • the louse was found by searching for a predetermined louse-shaped object in the form of a predetermined shape, as the one shown and described above with respect to fig. 3.
  • fig. 4 showing the user interface 40 of a computer program executed by the computer device 3.
  • this user interface is used for testing of the prototype of the method, and hence there are several possibilities for adjusting different threshold values in order to perform the image differentiating algorithm(s).
  • the user interface is showing a lot of information about the image to the user, which is strictly not necessary in order to detect whether or not a louse is present on the fish or to count the number of lice on a fish. It should therefore be noted that the method and system according to the present invention does not need a user interface like the one shown in fig. 4.
  • the user interface 40 contains a text box 42 where information is shown if a louse is detected.
  • the information contains the following information:
  • Y 1290 pixels (from the upper side of the image)) of the image, the height of the sub-image is 85 pixels and the length of the sub-image is 55 pixels.
  • the position of the louse is indicated by a dashed circle 43.
  • a color filter is used when performing step 12 and step 14.
  • the color filter typically defines a color interval with a minimum value and a maximum value for a color value.
  • the maximum and minimum values can be defined in any color system, such as RGB (selecting values for variables Red, Green, Blue), CMYK (selecting values for variables Cyan, Magenta, Yellow, Black), HSL (selecting values for variables Hue, Saturation, Light) or other color system.
  • the color interval can be defined as a minimum value and a maximum value for each variable in the color system or for only one variable in the color system.
  • a minimum value and a maximum value can be defined for additional properties such as opacity/transparency, reflexivity, etc.
  • the type of color filter and type of color system are considered known for a skilled person and will not be described here in detail.
  • step 12 and 14 there are libraries available in many programming languages. Moreover, shape recognition algorithms, alternatively image comparison algorithms, used in step 16, are considered known for a skilled person and will not be described here in detail. Libraries are available for implementing these algorithms in many programming languages as well.
  • the method may comprise the step of increasing a lice counter for each louse found in the image.
  • the method may comprise the step of counting the number of fish being taken images of, and hence perform the step of computing the average number of lice per fish.
  • a fast and efficient method and system for detecting a louse on a fish is achieved.

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  • Life Sciences & Earth Sciences (AREA)
  • Environmental Sciences (AREA)
  • Zoology (AREA)
  • Marine Sciences & Fisheries (AREA)
  • Animal Husbandry (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Image Analysis (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

La présente invention concerne un procédé de détection d'un pou sur un poisson, lequel procédé comprend les étapes consistant à recevoir une image d'un poisson ; à rechercher des pixels ayant des couleurs à l'intérieur d'un intervalle de couleurs d'arrière-plan et à régler ces pixels à une valeur de pixel par défaut ; à rechercher des pixels ayant des couleurs à l'intérieur d'un intervalle de couleurs de surface de poisson et à régler ces pixels à la valeur de pixel par défaut ; et à rechercher un objet en forme de pou prédéterminé dans ces parties de l'image ayant une valeur de pixel différente de la valeur par défaut. Ensuite, le procédé comprend l'étape consistant à déterminer si l'objet en forme de pou prédéterminé est ou non trouvé dans l'image. S'il est trouvé, le procédé réalise les étapes consistant à : fournir une sous-image de l'image, la sous-image contenant la zone de l'image dans laquelle l'objet en forme de pou prédéterminé est trouvé ; et stocker des informations concernant la sous-image, le stockage d'informations consistant à stocker des informations concernant la position de la sous-image dans l'image.
PCT/EP2012/068921 2011-10-12 2012-09-26 Procédé et système de détection d'un pou sur un poisson WO2013053597A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
NO20111385A NO333499B1 (no) 2011-10-12 2011-10-12 Fremgangsmate og system for a detektere en lus pa fisk
NO20111385 2011-10-12

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Cited By (11)

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EP2962556A1 (fr) 2014-06-30 2016-01-06 Ardeo Technology AS Système et procédé de surveillance et de lutte contre des ectoparasites de poissons
WO2017068127A1 (fr) * 2015-10-22 2017-04-27 Intervet International B.V. Procédé de contrôle automatique à la recherche de poux de mer dans le cadre d'un élevage de salmonidés
NO20151649A1 (en) * 2015-12-02 2017-06-05 Intervet Int Bv A method for automatic sea lice monitoring in salmon aquaculture
NO20160199A1 (no) * 2016-02-08 2017-08-09 Biosort As Anordning og fremgangsmåte for å registrere og overvåke helse og fysisk utvikling til levende fisk
CN109472883A (zh) * 2018-09-27 2019-03-15 中国农业大学 巡塘方法和装置
WO2019121887A1 (fr) * 2017-12-20 2019-06-27 Intervet International B.V. Système de surveillance des parasites externes de poisson en aquaculture
WO2019121900A1 (fr) * 2017-12-20 2019-06-27 Intervet Inc. Procédé et système de surveillance de parasites externes de poisson en aquaculture
CN111511202A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
CN111511201A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
CN111511203A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的方法和系统
RU2776717C2 (ru) * 2017-12-20 2022-07-25 Интервет Интернэшнл Б.В. Способ и система для мониторинга наружных паразитов рыб в аквакультуре

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NO20162016A1 (no) * 2016-12-19 2018-04-30 Henry Helgheim Anordning og fremgangsmåte til behandling av fisk i en oppdrettsmerd.

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WO2009008733A1 (fr) * 2007-07-09 2009-01-15 Feed Control Norway As Moyens et procédé de détermination du poids moyen et d'alimentation en fonction de l'appétit
WO2010087722A1 (fr) * 2009-01-30 2010-08-05 Feed Control Norway As Dispositif pour retirer des poux d'organismes aquatiques
WO2011115496A1 (fr) * 2010-02-05 2011-09-22 Esben Beck Procédé et dispositif pour la destruction de parasites sur un poisson

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EP1510125A1 (fr) * 2003-08-26 2005-03-02 Sociedad Comercial E Industrial Equa Limitada Procédé d'observation et de contrôle de nourriture non consommée en pisciculture
WO2009008733A1 (fr) * 2007-07-09 2009-01-15 Feed Control Norway As Moyens et procédé de détermination du poids moyen et d'alimentation en fonction de l'appétit
WO2010087722A1 (fr) * 2009-01-30 2010-08-05 Feed Control Norway As Dispositif pour retirer des poux d'organismes aquatiques
WO2011115496A1 (fr) * 2010-02-05 2011-09-22 Esben Beck Procédé et dispositif pour la destruction de parasites sur un poisson

Cited By (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2962556A1 (fr) 2014-06-30 2016-01-06 Ardeo Technology AS Système et procédé de surveillance et de lutte contre des ectoparasites de poissons
WO2017068127A1 (fr) * 2015-10-22 2017-04-27 Intervet International B.V. Procédé de contrôle automatique à la recherche de poux de mer dans le cadre d'un élevage de salmonidés
US20180303073A1 (en) * 2015-10-22 2018-10-25 Intervet Inc. A Method for Automatic Sea Lice Monitoring in Salmon Aquaculture
US11659821B2 (en) 2015-10-22 2023-05-30 Intervet Inc. Method for automatic sea lice monitoring in salmon aquaculture
US10863727B2 (en) 2015-10-22 2020-12-15 Intervet Inc. Method for automatic sea lice monitoring in salmon aquaculture
NO20151649A1 (en) * 2015-12-02 2017-06-05 Intervet Int Bv A method for automatic sea lice monitoring in salmon aquaculture
NO342604B1 (en) * 2015-12-02 2018-06-18 Intervet Int Bv A method for automatic sea lice monitoring in salmon aquaculture
NO20160199A1 (no) * 2016-02-08 2017-08-09 Biosort As Anordning og fremgangsmåte for å registrere og overvåke helse og fysisk utvikling til levende fisk
NO342993B1 (no) * 2016-02-08 2018-09-17 Biosort As Anordning og fremgangsmåte for å registrere og overvåke helse og fysisk utvikling til levende fisk
CN111511201A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
CN111491508B (zh) * 2017-12-20 2022-05-24 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
CN111511202A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
WO2019121900A1 (fr) * 2017-12-20 2019-06-27 Intervet Inc. Procédé et système de surveillance de parasites externes de poisson en aquaculture
CN111511203A (zh) * 2017-12-20 2020-08-07 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的方法和系统
CN111526716A (zh) * 2017-12-20 2020-08-11 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的方法和系统
WO2019121887A1 (fr) * 2017-12-20 2019-06-27 Intervet International B.V. Système de surveillance des parasites externes de poisson en aquaculture
CN111491508A (zh) * 2017-12-20 2020-08-04 英特维特国际股份有限公司 用于水产养殖中的鱼外部寄生虫监测的系统
RU2776717C2 (ru) * 2017-12-20 2022-07-25 Интервет Интернэшнл Б.В. Способ и система для мониторинга наружных паразитов рыб в аквакультуре
RU2777572C2 (ru) * 2017-12-20 2022-08-08 Интервет Интернэшнл Б.В. Система для мониторинга наружного паразита рыбы в аквакультуре
US11533893B2 (en) 2017-12-20 2022-12-27 Intervet Inc. Method and system for external fish parasite monitoring in aquaculture
US11632939B2 (en) 2017-12-20 2023-04-25 Intervet Inc. System for external fish parasite monitoring in aquaculture
US11980170B2 (en) 2017-12-20 2024-05-14 Intervet Inc. System for external fish parasite monitoring in aquaculture
US11825814B2 (en) 2017-12-20 2023-11-28 Intervet Inc. System for external fish parasite monitoring in aquaculture
US11849707B2 (en) 2017-12-20 2023-12-26 Intervet Inc. Method and system for external fish parasite monitoring in aquaculture
CN109472883A (zh) * 2018-09-27 2019-03-15 中国农业大学 巡塘方法和装置

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NO333499B1 (no) 2013-06-24

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