BR112018072122A2 - sistema para detecção de doenças de plantas, método implementado por computador para detectar doenças de plantas e produto de programa de computador para detecção de doença de plantas - Google Patents

sistema para detecção de doenças de plantas, método implementado por computador para detectar doenças de plantas e produto de programa de computador para detecção de doença de plantas

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Publication number
BR112018072122A2
BR112018072122A2 BR112018072122-0A BR112018072122A BR112018072122A2 BR 112018072122 A2 BR112018072122 A2 BR 112018072122A2 BR 112018072122 A BR112018072122 A BR 112018072122A BR 112018072122 A2 BR112018072122 A2 BR 112018072122A2
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Brazil
Prior art keywords
plant
image
module
disease detection
plant disease
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BR112018072122-0A
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English (en)
Other versions
BR112018072122A8 (pt
Inventor
Alexander Johannes
Eggers Till
Picon Artzai
Alvarez-Gila Aitor
Maria Ortiz Barredo Amaya
María Díez-Navajas Ana
Original Assignee
Basf Se
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Publication date
Application filed by Basf Se filed Critical Basf Se
Publication of BR112018072122A2 publication Critical patent/BR112018072122A2/pt
Publication of BR112018072122A8 publication Critical patent/BR112018072122A8/pt

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    • 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
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • 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
    • G01N33/0098—Plants or trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
    • G06F18/24155—Bayesian classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20076—Probabilistic image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30188—Vegetation; Agriculture

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Physics (AREA)
  • Chemical & Material Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biochemistry (AREA)
  • Pathology (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Molecular Biology (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Immunology (AREA)
  • Analytical Chemistry (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Multimedia (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Quality & Reliability (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Wood Science & Technology (AREA)
  • Botany (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

um sistema (100), método e produto de programa de computador para determinar doenças de plantas. o sistema inclui um módulo de interface (110) configurado para receber uma imagem (10) de uma planta, a imagem (10) incluindo uma representação visual (11) de pelo menos um elemento de planta (1). um módulo de normalização de cor (120) é configurado para aplicar um método de constância de cor à imagem recebida (10) para gerar uma imagem normalizada por cor. um módulo extrator (130) é configurado para extrair uma ou mais partes de imagem (11e) da imagem normalizada por cor, em que as partes de imagem extraídas (11e) correspondem ao pelo menos um elemento de planta (1). um módulo de filtragem (140) configurado: para identificar um ou mais agrupamentos (c1 a cn) por uma ou mais características visuais dentro das partes de imagem extraídas (11e), em que cada agrupamento está associado a uma parte de elemento de planta mostrando características de uma doença de plantas; e para filtrar uma ou mais regiões candidatas dos um ou mais agrupamentos identificados (c1 a cn) de acordo com um limiar predefinido, usando um classificador bayes que modela estatísticas de características visuais que estão sempre presentes em uma imagem de planta doente. um módulo de diagnóstico de doenças de plantas (150) configurado para extrair, usando um método de inferência estatística, de cada região candidata (c4, c5, c6, cn) uma ou mais características visuais para determinar, para cada região candidata, uma ou mais probabilidades indicando uma doença particular; e para calcular um escore de confiança (cs1) para a doença particular, avaliando todas as probabilidades determinadas das regiões candidatas (c4, c5, c6, cn).
BR112018072122A 2016-05-13 2017-04-19 Sistema para detecção de doenças de plantas, método implementado por computador para detectar doenças de plantas e meio legível por computador para detecção de doença de plantas BR112018072122A8 (pt)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP16169719 2016-05-13
EP16169719.8 2016-05-13
PCT/EP2017/059231 WO2017194276A1 (en) 2016-05-13 2017-04-19 System and method for detecting plant diseases

Publications (2)

Publication Number Publication Date
BR112018072122A2 true BR112018072122A2 (pt) 2019-02-12
BR112018072122A8 BR112018072122A8 (pt) 2023-04-04

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BR112018072122A BR112018072122A8 (pt) 2016-05-13 2017-04-19 Sistema para detecção de doenças de plantas, método implementado por computador para detectar doenças de plantas e meio legível por computador para detecção de doença de plantas

Country Status (9)

Country Link
US (1) US11037291B2 (pt)
EP (1) EP3455782B1 (pt)
CN (1) CN109154978B (pt)
AR (1) AR108473A1 (pt)
AU (1) AU2017264371A1 (pt)
BR (1) BR112018072122A8 (pt)
CA (1) CA3021795A1 (pt)
RU (1) RU2018142757A (pt)
WO (1) WO2017194276A1 (pt)

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RU2018142757A (ru) 2020-06-15
CA3021795A1 (en) 2017-11-16
US11037291B2 (en) 2021-06-15
WO2017194276A1 (en) 2017-11-16
CN109154978A (zh) 2019-01-04
US20200320682A1 (en) 2020-10-08
EP3455782A1 (en) 2019-03-20
AU2017264371A1 (en) 2018-11-01
EP3455782B1 (en) 2020-07-15
WO2017194276A9 (en) 2018-07-26
RU2018142757A3 (pt) 2020-08-19
CN109154978B (zh) 2023-04-11
AR108473A1 (es) 2018-08-22
BR112018072122A8 (pt) 2023-04-04

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