Desenvolvimento de descritores de imagens para reconhecimento de padrões de plantas invasoras (folhas largas e folhas estreitas)

AUTOR(ES)
DATA DE PUBLICAÇÃO

2009

RESUMO

In Brazil, the development of tools for weeds recognition, capable of aiding risk detection and decision making on the fieldwork is still embryonic. This masters thesis presents the development of a pattern recognition system that recognizes weeds and gives the occupation percentage of wide and narrow leaves in an agricultural production system, with digital image processing techniques. The development was based on considerations about image acquisition, pre-processing, texture based segmentation, descriptors for weeds recognition and occupation percentage of each kind of leaf. The validation has been developed considering geometric patterns generated in laboratory, as well as others obtained of a maize (Zea mays) production agricultural environment, i. e. two species of weeds, one with wide leaves (Euphorbia heterophylla L.) and other with narrow leaves (Digitaria sanguinalis Scop.). The results show recognition of about 84.24 percent for wide leaves and 80.17 percent for narrow leaves in agricultural environment and also the capability to spot weed on unreachable locations by natural vision. Besides, the method presents application in precision agriculture to improve the decision making in pulverization processes.

ASSUNTO(S)

processamento de imagens reconhecimento de padrões segmentação em textura texture segmentation processamento digital de imagens digital image processing erva daninha ciencia da computacao precision agriculture planta invasora weed agricultura de precisão pattern recognition

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