Data/hora: 11/06/2024 18:25:16

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	18/04/2005	
Data da última atualização: 	17/01/2020	
Autoria: 	CAMARGO NETO, J.; MEYER, G. E.; JONES, D. D.	
Afiliação: 	JOAO CAMARGO NETO, CNPTIA; GEORGE E. MEYER; DAVID D. JONES.	
Título: 	Advances in color image segmentation of plants for weed control.	
Ano de publicação: 	2004	
Fonte/Imprenta: 	In: ASAE/CSAE ANNUAL INTERNATIONAL MEETING, 2004, Ottawa. Dynamic partnerships for an environmentally safe and healthy world. St. Joseph, MI: American Society of Agricultural Engineers, 2004.	
Páginas: 	p. 1-16.	
Idioma: 	Inglês	
Notas: 	Paper number: 043060.	
Conteúdo: 	Abstract. A new and improved unsupervised plant segmentation index (ExGExR) is introduced. ExGRxR performance was compared with the traditional excess green segmentation method (ExG), using Otsu's method for automatic threshold. Segmentation accuracies were measured with a quality index, using a ground truth target plant mask, hand-generated for each image. Statistical results showed that there were significant differences in performance with bare soil backgrounds during the first week for pigweed and velvetleaf. For corn stalk residue, there were significant differences for all species during the first week and also significant differences during the second week for pigweed and velvetleaf. Using wheat straw residue background, there were significant differences for all species all three weeks. In general, the algorithm performed better than the ExG index for segmenting plants from soil-residues background.	
Palavras-Chave: 	Análise de imagem; Color index; Índice de cor; Segmentação; Segmentation.	
Thesagro: 	Planta; Resíduo.	
Thesaurus Nal: 	Image analysis; No-tillage.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (10669-1) - UPC - AA - -- -  -  - 2005.00009 - DES
CNPTIA - (10669-2) - UPC - AA - DD -  -  -  - DIS