Methodology of image analysis for study of the vertisols moisture content

Cumbrera Gonzalez, Ramiro Alberto; Milán Vega, Humberto y Tarquis Alfonso, Ana Maria (2014). Methodology of image analysis for study of the vertisols moisture content. En: "Actas del IX Congreso Internacional de Educación Superior. Del 10 al 14 de febrero de 2014, La Habana, Cuba.", 10/02/2014-14/02/2014, La Habana, Cuba. p. 11.

Descripción

Título: Methodology of image analysis for study of the vertisols moisture content
Autor/es:
  • Cumbrera Gonzalez, Ramiro Alberto
  • Milán Vega, Humberto
  • Tarquis Alfonso, Ana Maria
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: Actas del IX Congreso Internacional de Educación Superior. Del 10 al 14 de febrero de 2014, La Habana, Cuba.
Fechas del Evento: 10/02/2014-14/02/2014
Lugar del Evento: La Habana, Cuba
Título del Libro: 9º Congreso Internacional de Educación Superior
Fecha: 2014
Materias:
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Matemática Aplicada
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a ba re Mazic Pellic Vertisols ix of them in May 13/2011 and the rest in May 19 /2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak? camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents box counting dimension D BC) and interface fractal dimension (D) In addition, three pre-fractal scaling coefficients were determinate at maximum resolution: total number of boxes intercepting the foreground pattern (A), fractal lacunarity (?1) and Shannon entropy S1). For all the images processed the spatial filter 9x9 was the optimum based on entropy, cluster and histogram criteria. Thresholds for each color were selected based on bimodal histograms.

Más información

ID de Registro: 37058
Identificador DC: http://oa.upm.es/37058/
Identificador OAI: oai:oa.upm.es:37058
Depositado por: Memoria Investigacion
Depositado el: 03 Ago 2015 16:51
Ultima Modificación: 06 Jun 2016 16:51
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