Comparative assessment of feature selection and classification techniques for visual inspection of pot plant seedlings

Autor(es)

Silva, L. O. L. A. ^[1] ; Koga, M. L. ^[1] ; Cugnasca, C. E. ^[1] ; Costa, A. H. R. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Agr Automat Lab LAA, BR-05508900 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 97, p. 47-55, SEP 2013.
• Citações Web of Science: 14

Resumo

Homogeneity plays an important role in ornamental plant and flower production. As assessing the quality of seedlings is an effective way of predicting plant growth performance, a vision system capable of performing this task is desirable. Yet, the optical sorting of agricultural products must find ways to incorporate knowledge from human experts into the computational solution. Our aim is evaluating feature selection techniques with respect to the performance of vision-based inspection and classification of pot plant seedlings. A large feature set was initially obtained from seedlings images and several subsets were generated with various features selection techniques. The performance of each subset was compared to some of the most popular classifiers in the literature: Naive Bayes, k-Nearest Neighbors, Logistic Regression, C4.5, Random Forest, Multilayer Perceptron as well as Partial Least Squares and Support Vector Machine Discriminant Analysis. The best classifier and subset configuration is presented; our results show that feature selection was indeed advantageous, generating accuracy gains of up to 7.4%. (c) 2013 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 12/02190-9 - Transferência de Conhecimento entre Tarefas no Aprendizado por Reforço
• Beneficiário: Marcelo Li Koga
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 11/19280-8 - CogBot: integrando informação perceptual e conhecimento semântico na robótica cognitiva
• Beneficiário: Anna Helena Reali Costa
• Modalidade de apoio: Auxílio à Pesquisa - Regular