BR112023003968A2 - Método implementado por computador, produto de programa de computador e sistema de computador - Google Patents

Método implementado por computador, produto de programa de computador e sistema de computador

Info

Publication number
BR112023003968A2
BR112023003968A2 BR112023003968A BR112023003968A BR112023003968A2 BR 112023003968 A2 BR112023003968 A2 BR 112023003968A2 BR 112023003968 A BR112023003968 A BR 112023003968A BR 112023003968 A BR112023003968 A BR 112023003968A BR 112023003968 A2 BR112023003968 A2 BR 112023003968A2
Authority
BR
Brazil
Prior art keywords
damage
real
plant
world image
computer
Prior art date
Application number
BR112023003968A
Other languages
English (en)
Inventor
Piotr Schikora Marek
Bender Martin
Zies Maik
Wildt Joerg
Wahabzada Mirwaes
Original Assignee
Basf Agro Trademarks 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 Basf Agro Trademarks Gmbh filed Critical Basf Agro Trademarks Gmbh
Publication of BR112023003968A2 publication Critical patent/BR112023003968A2/pt

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/55—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23—Updating
    • G06F16/2379—Updates performed during online database operations; commit processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/587—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
    • G06V10/758—Involving statistics of pixels or of feature values, e.g. histogram matching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/761—Proximity, similarity or dissimilarity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/7715—Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/94—Hardware or software architectures specially adapted for image or video understanding
    • G06V10/945—User interactive design; Environments; Toolboxes
    • 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
    • G06V20/60—Type of objects
    • G06V20/68—Food, e.g. fruit or vegetables
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/10—Recognition assisted with metadata

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Multimedia (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Medical Informatics (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Economics (AREA)
  • Animal Husbandry (AREA)
  • Tourism & Hospitality (AREA)
  • Strategic Management (AREA)
  • Primary Health Care (AREA)
  • Marketing (AREA)
  • Human Resources & Organizations (AREA)
  • Mining & Mineral Resources (AREA)
  • Marine Sciences & Fisheries (AREA)
  • General Business, Economics & Management (AREA)
  • Agronomy & Crop Science (AREA)
  • Library & Information Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Image Analysis (AREA)
  • Processing Or Creating Images (AREA)

Abstract

MÉTODO IMPLEMENTADO POR COMPUTADOR, PRODUTO DE PROGRAMA DE COMPUTADOR E SISTEMA DE COMPUTADOR. Método e sistema implementados por computador (100) para aprimorar um banco de dados de imagens de plantas (230) para melhor identificação de danos em plantas. O sistema recebe uma imagem do mundo real (91) de uma planta (11), gravada em uma determinada localização geográfica (2), em conjunto com metadados de imagem compreendendo dados de localização (LD1) indicando a determinada localização geográfica (2), e um carimbo de hora (TS1) indicando o ponto no tempo (3) quando a imagem do mundo real (91) foi gravada. Um identificador de danos (110), treinado para identificar classes de danos associadas a sintomas de danos presentes em plantas de determinadas espécies de plantas, gera, a partir da imagem do mundo real (91), uma saída incluindo uma classe de danos (DC1) para os sintomas de danos na imagem do mundo real. Um verificador de similaridade (120) determina semelhanças de características da imagem do mundo real com imagens selecionadas (232, 233, 234, 235) em um banco de dados de imagens de plantas (230) e identifica ainda pelo menos um subconjunto (230s) das imagens selecionadas tendo uma semelhança de característica com a imagem do mundo real que excede um valor mínimo de semelhança (124). A classe de danos gerada (DC1) e as imagens do subconjunto (230s) com as respectivas classes de danos e identificador de espécie de planta são fornecidos a um usuário (9). Em resposta, o sistema recebe do usuário (9) uma classe de danos confirmada (CDC1) para a imagem do mundo real (91). Um atualizador de banco de dados (140) do sistema atualiza o banco de dados de imagem de planta (230) armazenando a imagem do mundo real (91) recebida em conjunto com seu identificador de espécie de planta, seus dados de localização, seu carimbo de hora e a classe de danos confirmada.
BR112023003968A 2020-09-04 2021-09-02 Método implementado por computador, produto de programa de computador e sistema de computador BR112023003968A2 (pt)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP20194648 2020-09-04
PCT/EP2021/074258 WO2022049190A1 (en) 2020-09-04 2021-09-02 System and method for enhancing a plant image database for improved damage identification on plants

Publications (1)

Publication Number Publication Date
BR112023003968A2 true BR112023003968A2 (pt) 2023-04-11

Family

ID=72381027

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112023003968A BR112023003968A2 (pt) 2020-09-04 2021-09-02 Método implementado por computador, produto de programa de computador e sistema de computador

Country Status (5)

Country Link
US (1) US20240020331A1 (pt)
EP (1) EP4208819A1 (pt)
JP (1) JP2023541124A (pt)
BR (1) BR112023003968A2 (pt)
WO (1) WO2022049190A1 (pt)

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017194276A1 (en) 2016-05-13 2017-11-16 Basf Se System and method for detecting plant diseases
US10438302B2 (en) * 2017-08-28 2019-10-08 The Climate Corporation Crop disease recognition and yield estimation

Also Published As

Publication number Publication date
EP4208819A1 (en) 2023-07-12
WO2022049190A1 (en) 2022-03-10
US20240020331A1 (en) 2024-01-18
JP2023541124A (ja) 2023-09-28

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