In field soil characterization: Approach based on texture image analysis

被引:18
|
作者
Breul, P [1 ]
Gourves, R [1 ]
机构
[1] Univ Clermont Ferrand, LGC Civil Engn Lab, F-63174 Aubiere, France
关键词
D O I
10.1061/(ASCE)1090-0241(2006)132:1(102)
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Building on the development of a tool for in place soil investigation based on the use of endoscopy, this paper presents a method for soil characterization using the images recorded by this tool. Various techniques have been explored including texture analysis which is very attractive because it is based on global image analysis. The use of a third order moment resulting from spectral analysis and its value for soil characterization is presented. The influence of various parameters (particle size distribution, mineralogy, water content, and compaction) on the moment evolution is studied.
引用
收藏
页码:102 / 107
页数:6
相关论文
共 50 条
  • [11] Gabor wavelet image analysis for soil texture classification
    Sun, Y
    Long, ZL
    Jang, PR
    Plodinec, MJ
    NONDESTRUCTIVE SENSING FOR FOOD SAFETY, QUALITY, AND NATURAL RESOURCES, 2004, 5587 : 254 - 261
  • [12] A texture analysis approach to corrosion image classification
    Livens, S
    Scheunders, P
    VandeWouwer, G
    VanDyck, D
    Smets, H
    Winkelmans, J
    Bogaerts, W
    MICROSCOPY MICROANALYSIS MICROSTRUCTURES, 1996, 7 (02): : 143 - 152
  • [13] A Fractal-Based Approach to Network Characterization Applied to Texture Analysis
    Ribas, Lucas C.
    Manzanera, Antoine
    Bruno, Odemir M.
    COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2019, PT I, 2019, 11678 : 129 - 140
  • [14] A vegetation height classification approach based on texture analysis of a single VHR image
    Petrou, Z. I.
    Manakos, I.
    Stathaki, T.
    Tarantino, C.
    Adamo, M.
    Blonda, P.
    35TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT (ISRSE35), 2014, 17
  • [15] A Conditional Random Field Approach to Unsupervised Texture Image Segmentation
    Chang-Tsun Li
    EURASIP Journal on Advances in Signal Processing, 2010
  • [16] A Conditional Random Field Approach to Unsupervised Texture Image Segmentation
    Li, Chang-Tsun
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2010,
  • [17] Geostatistical Analysis of Soil Texture Fractions on the Field Scale
    Delbari, Masoomeh
    Afrasiab, Peyman
    Loiskandl, Willibald
    SOIL AND WATER RESEARCH, 2011, 6 (04) : 173 - 189
  • [18] Automatic characterization of nanofiber assemblies by image texture analysis
    Facco, Pierantonio
    Tomba, Emanuele
    Roso, Martina
    Modesti, Michele
    Bezzo, Fabrizio
    Barolo, Massimiliano
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2010, 103 (01) : 66 - 75
  • [19] Characterization of feldspar texture and liberation by automated image analysis
    Matos, MJ
    Lastra, R
    Petruk, W
    TRANSACTIONS OF THE INSTITUTION OF MINING AND METALLURGY SECTION C-MINERAL PROCESSING AND EXTRACTIVE METALLURGY, 1996, 105 : C133 - C140
  • [20] Field-based soil-texture estimates could replace laboratory analysis
    Vos, Cora
    Don, Axel
    Prietz, Roland
    Heidkamp, Arne
    Freibauer, Annette
    GEODERMA, 2016, 267 : 215 - 219