A vision-based method for weeds identification through the Bayesian decision theory

Tellaeche, Alberto; Burgos-Artizzu, Xavier P.; Pajares, Gonzalo; Ribeiro, Ángela

doi:10.1016/j.patcog.2007.07.007

Cited by 130 publications

(75 citation statements)

References 21 publications

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“…Inúmeras tecnologias têm sido desenvolvidas tentando obter maior eficiência na aplicação de herbicidas e redução dos impactos no meio ambiente, dentre as quais pode-se citar a definição de unidades de gerenciamento diferenciado para aplicação de herbicidas (Tellaeche et al, 2008). Entretanto, grande parte das pesquisas associadas à agricultura de precisão no controle de plantas daninhas tem sido realizada no exterior.…”

Section: Considerações Finais E Perspectivasunclassified

Biologia e manejo de plantas daninhas em áreas de plantio direto

Gomes

Christoffoleti

2008

Planta daninha

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RESUMO -Procurou-se relacionar alguns aspectos importantes da biologia e do manejo das plantas daninhas infestantes em áreas cultivadas sob sistema de plantio direto, com o objetivo de mostrar que a viabilidade deste plantio depende do controle eficiente das plantas daninhas. Nesse sistema de cultivo ocorrem algumas espécies de plantas daninhas comumente não observadas no sistema convencional, sendo essas constatações relacionadas ao não-revolvimento do solo, favorecendo o desenvolvimento de espécies de plantas daninhas perenes, e às alterações nas condições de temperatura e incidência de luz no interior do solo, influenciando os mecanismos de dormência das sementes de algumas espécies. A estratégia adequada para o controle das plantas daninhas em plantio direto exige conhecimento da dinâmica populacional do banco de sementes do solo e deve reunir métodos integrados de controle para reduzir o uso de herbicidas. A liberação de substâncias alelopáticas de algumas culturas de cobertura e o efeito supressor da camada de palha são medidas importantes para integrar ao controle químico das plantas daninhas. Entretanto, deve-se atentar para os efeitos negativos sobre algumas espécies de plantas cultivadas. As pesquisas na área de biologia das plantas daninhas e alelopatia das culturas de cobertura, associadas com a tecnologia de aplicação de herbicidas e a agricultura de precisão, poderão contribuir para a otimização do controle das plantas daninhas em áreas de plantio direto.Palavras-chave: semeadura direta, banco de sementes, palhada, glyphosate.ABSTRACT -Some important aspects of weed biology and control under no tillage are described to show that the viability of this system depends on weed control efficiently performed. Some of the weeds infesting this cropping system are present in much greater density under the conventional system, this being probably due to the little soil disturbance under no tillage systems, where the occurrence of perennial weeds is more feasible, and changes in the temperature and light incidence on the soil surface influence dormancy of some weed species. Adequate strategy for weed control under the no tillage system requires knowledge on weed seed bank dynamics and must integrate methods of weed control in order to reduce the use of herbicides. The release of alellopathic compounds by some of the cover crops and the suppressive effects of crop residue cover are important measures in order to integrate the chemical control of weeds. However, it is important to be aware of the negative impacts over certain cultivated species of plants. Studies on weed biology and alellopathy of cover crops, associated to herbicide application technology and precision agriculture may contribute to weed control optimization in areas under no tillage system.

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Section: Considerações Finais E Perspectivasunclassified

Biologia e manejo de plantas daninhas em áreas de plantio direto

Gomes

Christoffoleti

2008

Planta daninha

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“…However, in this context, the crop rows are roughly approximated by lines, while for weed patch detection the precision required is much higher. Some other works use the Hough transform (Gonzalez and Woods, 2003), to fully locate the crop rows and then label the rest of vegetation pixels as weeds (Leemans and Destain, 2006;Tellaeche et al, 2008b;Gée et al, 2008;Bakker et al, 2008). The drawback of this approach is the high computational complexity of the Hough transform, which makes it unsuitable for applications in which there is a need to process images in real-time, i.e.…”

Section: Introductionmentioning

confidence: 99%

Real-time image processing for crop/weed discrimination in maize fields

Burgos-Artizzu

Ribeiro

Guijarro

et al. 2011

Computers and Electronics in Agriculture

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254

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Keywords:Computer vision Precision Agriculture Weed detection Real-time image processing This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving.

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“…340 images were used in [18], 146 in [19] and 120 in [21]. This is in relation to the advantages exposed in Section 2.2.3 regarding the computational complexity and information storage.…”

Section: Comparative Analysis and Performance Evaluationmentioning

confidence: 96%

“…From the above, several systems have been designed to solve this problem using automatic vision strategies and various machine learning techniques to identify areas with avena sterilis which must be selectively sprayed [15][16][17][18][19][20][21]. Despite the good performance of these systems, all of them share a common inconvenient, the techniques used to take a decision are very demanding from a computational point of view.…”

Section: Introductionmentioning

confidence: 99%

A computer vision approach for weeds identification through Support Vector Machines

Tellaeche

Pajares

Burgos-Artizzu

et al. 2011

Applied Soft Computing

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131

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Keywords: Support Vector Machines Machine vision Weed identification Image segmentation Decision makingThis paper outlines an automatic computer vision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the Support Vector Machines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the Support Vector Machines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

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A vision-based method for weeds identification through the Bayesian decision theory

Cited by 130 publications

References 21 publications

Biologia e manejo de plantas daninhas em áreas de plantio direto

Biologia e manejo de plantas daninhas em áreas de plantio direto

Real-time image processing for crop/weed discrimination in maize fields

A computer vision approach for weeds identification through Support Vector Machines

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