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Artificial vision system for plant nutricional state identification

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Author(s):
Alvaro Manuel Gómez Zúñiga
Total Authors: 1
Document type: Master's Dissertation
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
Defense date:
Examining board members:
Odemir Martinez Bruno; Pedro Henrique de Cerqueira Luz; Agma Juci Machado Traina
Advisor: Odemir Martinez Bruno
Abstract

The evaluation of the nutritional status of corn plants is usually done through chemical analysis or by visual diagnosis of the plant leaves. Visual diagnosis is subject to misinterpretation as the lack of some nutrient in the plant generates a specific pattern of change in the leaf surface that depends on the degree on which the nutrient is absent on the plant. The difficulties present in this process and its importance in agriculture creates the necessity to search automated systems for the assessment of nutritional status of plants. Thus, this dissertation had as main objective the development of an artificial vision system to verify the possibility of identifying levels of macronutrients calcium, sulfur, magnesium, potassium and nitrogen in corn plants by analyzing the surface of the leaves using computer vision methods. This project performs a review of the literature of the state of the art methods for feature extraction of color, grayscale and colored texture used in image processing. The high similarity between the symptoms caused by deficiencies and low similarity between samples of the same deficiency motivated the development of new methods for extracting features that could provide the data needed for a correct separation between classes. The results showed that the system enables the prediction of nutritional deficiencies in an initial stage of plant growth using only texture of the leaf surface as a source of information (AU)

FAPESP's process: 09/04362-9 - ARTIFICIAL VISION SYSTEM FOR IDENTIFICATION OF NUTRITIONAL STATE IN CORN PLANTS
Grantee:Alvaro Manuel Gómez Zúniga
Support Opportunities: Scholarships in Brazil - Master