EP3688660A1 - Procédé de détection d'un bord de feuille, procédé pour le traitement ciblé de plantes au moyen d'un agent foliaire et utilisation d'un capteur d'images à base d'évènements pour la détection d'un bord de feuille - Google Patents

Procédé de détection d'un bord de feuille, procédé pour le traitement ciblé de plantes au moyen d'un agent foliaire et utilisation d'un capteur d'images à base d'évènements pour la détection d'un bord de feuille

Info

Publication number
EP3688660A1
EP3688660A1 EP18765629.3A EP18765629A EP3688660A1 EP 3688660 A1 EP3688660 A1 EP 3688660A1 EP 18765629 A EP18765629 A EP 18765629A EP 3688660 A1 EP3688660 A1 EP 3688660A1
Authority
EP
European Patent Office
Prior art keywords
pixel
event
plant
polarity
image
Prior art date
Legal status (The legal status 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 status listed.)
Ceased
Application number
EP18765629.3A
Other languages
German (de)
English (en)
Inventor
Gregor Blott
Damian Koesters
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
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 Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP3688660A1 publication Critical patent/EP3688660A1/fr
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/188—Vegetation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/194—Terrestrial scenes using hyperspectral data, i.e. more or other wavelengths than RGB

Definitions

  • Spectral range a sheet edge can be reliably detected.
  • the method it is determined that a leaf margin has been detected if the first pixel at a first time tl at least one event of a first Polarity and the second pixel detected at a time t2 at least one event of a second polarity, wherein the first and second polarity are opposite, and that the at least one event of a first polarity of the first pixel and the at least one event of a second polarity of the second pixel the same Place of plant-covered soil corresponds.
  • the term "the same place is to be understood as meaning the plant-covered ground", in particular adjacent pixels of a single image, or alternatively pixels with a spacing of up to three pixels can be understood Plant-covered soil both in the first and in the second
  • intensity changes at the individual pixel positions represent events.
  • a detected event is sent immediately to a computing unit with microsecond accuracy and millisecond latency. If only the two adjacent pixels are considered in the time period, the event-based image sensor provides a time-dependent function for each pixel, which indicates for each time point whether an event was detected or not. If an event has been detected, the function additionally gives the
  • the events are detected with an event-based image sensor.
  • the event-based image sensor is preferably a DVS sensor. Since the detected events usually require much less memory than the
  • a plant height of a plant is determined from at least one image of the soil covered with plants.
  • an image is understood as an image taken with an event-based image sensor.
  • the stature height is determined from a variety of images of the vegetated soil with soil. The prerequisite for this is that an interpretable flow field can be determined from the at least one image.
  • SfM Structure from motion
  • the determination of the stature height has the advantage that subsequent spraying operations can be dosed more accurately and thus can be flexibly adapted to the particular circumstances.
  • Foliar treatment agent recognizes a sheet edge in a first step of the method according to the method set out above.
  • a leaf shape of the plant is detected based on the recognized leaf margin of the plant.
  • a leaf margin is detected for each pixel pair in which only one pixel predominantly detects events. Accordingly, any location of the sheet edge can be recognized for the entire still image. If each location of the leaf margin is known, a leaf shape can be determined or recognized. For a moving image, a leaf shape can be determined for each time you see the leaf.
  • a classification of the plant is determined on the basis of the specific leaf shape of the plant. This has the advantage that the thus classified plant can be specifically treated with a suitable agent for this plant.
  • Classification of the plant appropriate means treated. This advantageously ensures that certain plants are selective or targeted can be treated. For example, it is possible for weeds to be specifically treated with a weed control or herbicide. Alternatively or additionally, other recognized plants may be treated by other means.
  • Such agent is especially a pesticide, a pesticide, an insecticide, a fungicide, a herbicide, a biocide, a bactericide
  • Virucide an acaricide, an avicide, a molluscicide, a nematicide, an ovicide or a rodenticide.
  • the targeted treatment of the plant with a suitable agent for this plant has the advantage that no resources are wasted, in particular no plants are damaged because no plant is treated with an inappropriate agent.
  • the computer program is set up to perform each step of the method, especially when running on an electronic controller or computing device. This refers to both the method for the detection of a leaf margin and the method for the targeted treatment of plants with a foliar treatment agent. This allows the implementation of the method in a conventional control unit, without constructive
  • FIG. 1 shows a flowchart of a method for sheet edge detection according to an exemplary embodiment of the invention.
  • FIG. 1 shows a flow chart of a method 100 for sheet edge detection.
  • a first step 110 of the method 100 events of an image of a vegetated soil at a ground speed relative to the ground are detected using an event-based image sensor.
  • the ground resolution used here is 0.5 mm per pixel and in front of the image sensor, an NDVI-optimized color filter array (CFA) of bandpass filters in the NI R and R spectral range is arranged.
  • the NI R band pass filter is centered around 850 nm and the R band pass filter centered at 660 nm.
  • a sheet edge was detected if the detected events of two adjacent pixels were detected predominantly only at one of the two adjacent pixels.
  • Step 120 is performed for all adjacent pixels of the captured events of the image. This also means that the method 100 repeatedly measures a passing object. Thus, one obtains the leaf margin for all recorded images of the plant, from which one can determine a leaf shape of the plant. In step 130 of the method 100, a plant height of a plant is determined from all images showing the same plant of the overgrown soil.
  • a machine-based learning algorithm is used to classify the plant based on the images of the leaf margin taken by the plant.
  • the classified plant is specifically treated with a leaf treatment agent corresponding to the classification of the plant.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Image Processing (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

L'invention concerne un procédé (100) de détection d'un bord de feuille comprenant les étapes suivantes : la détection (110) d'évènements d'une image d'un sol recouvert de plantes à une certaine vitesse de déplacement par rapport au sol, une résolution du sol de l'image étant comprise entre 0,5 et 1 mm par pixel ; un filtre passe-bande d'une première plage de fréquences étant disposé devant un premier pixel de l'image et un filtre passe-bande d'une deuxième plage de fréquences étant disposé devant un deuxième pixel de l'image ; et la détermination (120) qu'un bord de feuille a été détecté, si le premier pixel détecte à un premier moment t1 au moins un évènement d'une première polarité et le deuxième pixel détecte à un moment t2 au moins un évènement d'une deuxième polarité, la première polarité et la deuxième polarité étant opposées, et que l'au moins un évènement d'une première polarité du premier pixel et l'au moins un événement d'une deuxième polarité du deuxième pixel correspondent au même emplacement du sol recouvert de plantes, ou si les évènements détectés n'ont été identifiés que dans le premier ou dans le deuxième pixel. L'invention concerne en outre un utilisation d'un capteur d'images à base d'évènements pour la détection bord de feuille, un programme informatique, un support de stockage lisible par machine et un appareil de commande électronique.
EP18765629.3A 2017-09-28 2018-09-06 Procédé de détection d'un bord de feuille, procédé pour le traitement ciblé de plantes au moyen d'un agent foliaire et utilisation d'un capteur d'images à base d'évènements pour la détection d'un bord de feuille Ceased EP3688660A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102017217275.4A DE102017217275A1 (de) 2017-09-28 2017-09-28 Verfahren zur Erkennung eines Blattrandes, Verfahren zur gezielten Behandlung von Pflanzen mit einem Blattbehandlungsmittel und Verwendung eines eventbasierten Bildsensors zur Erkennung eines Blattrandes
PCT/EP2018/073932 WO2019063255A1 (fr) 2017-09-28 2018-09-06 Procédé de détection d'un bord de feuille, procédé pour le traitement ciblé de plantes au moyen d'un agent foliaire et utilisation d'un capteur d'images à base d'évènements pour la détection d'un bord de feuille

Publications (1)

Publication Number Publication Date
EP3688660A1 true EP3688660A1 (fr) 2020-08-05

Family

ID=63517892

Family Applications (1)

Application Number Title Priority Date Filing Date
EP18765629.3A Ceased EP3688660A1 (fr) 2017-09-28 2018-09-06 Procédé de détection d'un bord de feuille, procédé pour le traitement ciblé de plantes au moyen d'un agent foliaire et utilisation d'un capteur d'images à base d'évènements pour la détection d'un bord de feuille

Country Status (4)

Country Link
EP (1) EP3688660A1 (fr)
BR (1) BR112020002571A2 (fr)
DE (1) DE102017217275A1 (fr)
WO (1) WO2019063255A1 (fr)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112256951A (zh) * 2020-09-09 2021-01-22 青岛大学 一种智能居家苗芽种植系统
DE102020215415A1 (de) 2020-12-07 2022-06-09 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Vorrichtung zum Detektieren einer Störpflanzenabbildung in einem Kamerarohbild und Bildverarbeitungseinrichtung

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9075008B2 (en) * 2003-11-07 2015-07-07 Kyle H. Holland Plant treatment based on a water invariant chlorophyll index
WO2012122988A1 (fr) * 2011-03-16 2012-09-20 Syddansk Universitet Rampe de pulvérisation pour pulvériser de manière sélective une composition désherbante sur des dicotylédones
WO2015006675A2 (fr) * 2013-07-11 2015-01-15 Blue River Technology, Inc. Procédé de mesure et de sélection automatique de phénotypes
US9336584B2 (en) * 2014-06-30 2016-05-10 Trimble Navigation Limited Active imaging systems for plant growth monitoring

Also Published As

Publication number Publication date
BR112020002571A2 (pt) 2020-08-04
WO2019063255A1 (fr) 2019-04-04
DE102017217275A1 (de) 2019-03-28

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