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Use of Image Analysis Methods in Geotechnical Engineering

Yıl 2018, Cilt: 9 Sayı: 1, 33 - 44, 17.01.2018
https://doi.org/10.29048/makufebed.345053

Öz

Image processing
technology includes transferring of images of objects to a computer and to
process by the computer for particular objectives. Image analysis, which aims
to mimick tasks that the human eye can do, is one of the most popular subjects
for today’s scientists and engineers. In recent years, with increasing rate, it
is used in geotechnical engineering for solutions such as deformation
measurements, shear analysis, porosity analysis, to determine particle size and
shape parameters, to determine geotextile characteristics. In this study;
possible use of image analysis methods in the solution of the problems
encountered geotechnical engineering was investigated. Literature on the use of
the image analysis as a complementary method, during identification and reveal
of mechanical behavior of rocks and soils in the laboratory and in the field
was evaluated, advantages and limitations were discussed.

Kaynakça

  • Al-Harthi, A.A., Al-Amri, R.M., Shehata, W.M. (1999). The porosity and engineering properties of vesicular basalt in Saudi Arabia. Engineering Geology, 54: 313– 320.
  • Al-Rousan T. M. (2004). Characterizatıon of aggregate shape properties usıng a computer automated system, Doctor of Philosophy, Texas A&M University, Civil Engineering, 211, Texas.
  • Alshibli, K. A., Al-Hamdan, M. Z. (2001). Estimating volume change of triaxial soil specimens from planar images, Computer-Aided Civil and Infrastructure Engineering, 16(6): 415-421.
  • Alshibli, K.A., Alsaleh, M.I. (2004). Characterizing surface roughness and shape of sands using digital microscopy, Journal of Computing in Civil Engineering, 18 (1): 36-45.
  • Alshibli, K.A., Batiste, S.N., Sture, S. (2003). Strain localization in sand: plane strain versus triaxial compression, Journal of Geotechnical and Geoenvorimental Engineering, ASCE, 129(6): 483-494.
  • Alshibli, K. A., Sture, S. (2000) Shear Band Formation in Plane Strain Experiments of Sand, ASCE, Journal of Geotechnical & Geoenvironmental Engineering, 126(6), 495-503.
  • ASTM C97, Standard Test Methods for Absorption and Bulk Specific Gravity of Dimension Stone, ASTM Standards, ASTM International, Philadelphia, USA.
  • ASTM D 427-83, Standard test method for shrinkage factors of soil, ASTM Standards, ASTM International, Philadelphia, USA.
  • ASTM D 4943-02, Standard Test Method for Shrinkage Factors of Soils by the Wax Method, ASTM Standards, ASTM International, Philadelphia, USA.
  • Aydilek, A.H. (2006). A semi-analytical model for development of woven geotextile filter selection criteria. Geosynthetics International, 13(2): 59–72.
  • Aydilek, A.H. Edil, T.B. (2004). Evaluation of Woven Geotextile Pore Structure Parameters Using Image Analysis, Geotechnical Testing Journal, 27(1): 1-12.
  • Aydilek, A.H., Kutay, M.E., Sparacino, R., Dafla, H. (2007). Image Analysis for QC/QA of Geosynthetic Deformation during Wide Width Tensile Testing, Proceedings of Geosynthetics 2007, Washington, D.C.
  • Aydilek, A.H., Oguz, S.H., Edil, T.B. (2005). Constriction size of geotextile filters. Journal of Geotechnical and Geoenvironmental Engineering, ASCE 131(1): 28–38.
  • Baxes, G.A. (1994). Digital image processing, principles and applications. 452 s., John Wiley & Sons, Inc., USA.
  • Beucher, S., Lantuejoul, C. (1979). Use of watersheds in contour detection. In the Proceedings of the international Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, Rennes, France.
  • Bhatia, S., Soliman, A. (1990). Frequency distribution of void ratio of granular materials determined by an image analyzer, Soils and Foundations, 30(1): 1-16.
  • Brzezicki, J. ve Kasperkiewicz, J. (1999). Automatic image analysis in evaluation of aggregate shape, Journal of Computing in Civil Engineering, 13(2), 123-128.
  • Castelman, R. K. (1996). Digital image processing. Prentice hall, Englewood Cliffs, New Jersey, USA.
  • Cheng, Y.P., White, D.J., Bowman, E.T., Bolton, M.D., Soga, K. (2001). The observation of soil microstructure under load, 4th International Conference on Micromechanics of Granular Media-Powders & Grains 2001, Kishino Y. (Ed): 69-72.
  • Crabtree, S.J., Ehrlich, Jr.R., Prince, C. (1984). Evaluation of strategies for segmentations of reservoir rocks, Computers Vision, Graphics and Image Processing, 28(1): 1-18.
  • Dipova N. (2014). Digital Image Analysis Based Porosity Measurement On Macro-Porous Rocks, V. Global Stone Congress, Antalya, 22-25 Ekim 2014, pp.70-70
  • Dipova, N. (2017a). Determining the grain size distribution of granular soils using image analysis, Acta Geotechnica Slovenica, 14: 28-37.
  • Dipova, N. (2017b). Görüntü analizi tekniklerinin serbest basınç dayanımı deneyinde kullanımı, 7. Geoteknik Sempozyumu 22-23-24 Kasım 2017, İstanbul.
  • Erhardt, A. (2000). Theory and Applications of Digital Image Processing, University of Applied Sciences, 54p.
  • Freilich, B., Zornberg, J.G. (2010). A Model for the Characterization of Scrap the Scrap Tire Bale Interface, Proceedings of the GeoFlorida 2010 Conference (GSP 199), Geo-Institute, ASCE, February 20-24, p. 2933-2942.
  • Frost, J.D., Jang, D.-J. (2000). Evolution of sand microstructure during shear. ASCE Jorurnal of Geotechnical and Geoenvironmental Engineering, 126(2): 116-130.
  • Ghalib, A.M., Hryciw, R.D. (1999). Soil partical size distribution by mosaic imaging and watershed analysis, Journal of Computing in Civil Engineering,13(2): 80-87.
  • Goodman, R. E., Ahlgren, C. S. (2000). Evaluating safety of concrete gravity dam on weak rock: Scott Dam, Journal of Geotechnical and Geoenvironmental Engineering, 126(5): 429–442.
  • Gonzalez, R. F., Woods R. E. (2001). Digital Image Processing, Prentice Hall, USA.
  • Güler, M., Edil, T.B., Bosscher P.J. (1999). Measurement of particle movement in granular soils using image analysis, ASCE Journal of Computing in Civil Engineering, 13 (2): 116-122.
  • Haneberg, W.C. (2004). Simulation of 3-D block populations to characterize outcrop sampling bias in block-in-matrix rocks (bimrocks), Felsbau-Rock and Soil Engineering, 22: 19–26.
  • Hryciw R.D., Raschke S.A. (1996). Development of a computer vision technique for insitu soil chracterization, Transportation Research Record, 1526: 86-97.
  • Hyoungkwan K., Haas, K.T., Rauch, A.F., Browne, C. (2003). 3D image segmentation of aggregates from laser profiling, Computer-Aided Civil and Infrastructure Engineering, 18: 254-263.
  • Hu, R.L., Yue, Z.Q., Tham, L.G., Wang, L.C. (2005). Digital image analysis of dynamic compaction effects on clay fills, ASCE Journal of Geotechnical and Geoenvironmental Engineering,131(11):1411-1422.
  • Kahraman, S., Alber, M., Fener, M., Gunaydin, O. (2010). The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis, Expert Systems with Applications, 37: 8750–8756.
  • King, R.P. (1984). Measurement of particle size distribution by image analyser, Powder Technology, 39(2): 279-289.
  • Kuo, C.Y., Frost, J.D. (1996). Uniformity evaluation of cohesionless specimens using digital image analysis. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 122(5), 390–396.
  • Kwan, A.K.H., Mora, C.F. Chan, H.C. (1999). Particle shape analysis of coarseaggregate using digital image processing, Cement and Concrete Research. 29(9): 1403-1410.
  • Macari, E. M., Parker, J. K., Costes, N. C. (1997). Measurement of volume changes in triaxial tests using digital imaging tecniques, Geotecnical Testing Journal, 20(1): 103-109.
  • Medley, E. W. (2002). Estimating block size distribution of melanges and similar block-in-matrix rocks (bimrocks). In R. Hammah, W. Bawden, J. Curran, & M. Telesnicki (Eds.), Proceedings of the 5th North American rock mechanics symposium (pp. 509–516). Toronto, Canada: University of Toronto Press.
  • Mertens, G., Elsen, J. (2006). Use of computer assisted image analysis for the determination of the grain-size distribution of sands used in mortars, Cement and Concrete Research, 36: 1453-1459.
  • Mora, C.F., Kwan, A.K.H., Chan, H.C. (1998). Particle size distribution analysis of coarse aggregate using digital image processing, Cement and Concrete Research, 28(6), 921-932.
  • Mora, C.F., Kwan, A.K.H. (2000). Sphericity, Shape Factor, and Convexity Measurement of Coarse Aggregate for Concrete Using Digital Image Processing, Cement and Concrete Research 30 (3): 351-358.
  • Muhunthan, B., Masad, E., Asaad, A. (2000). Measurement of uniformity and anisotropy in granular materials, Geotechncal Testing Journal, 23(4), 423-431.
  • Nielsen, B.D. (2004). Non-Destructive soil testing using X-ray Computed Tomography, M.S. Thesis, Montana State University, Bozeman, Montana.
  • Ören, A. H., Önal, O., Özden, G., Kaya, A. (2006). Nondestructive evaluation of volumetric shrinkage of compacted mixtures using digital image analysis, Engineering Geology, 85(3-4), 239-250.
  • Peng, X., Horn, R., Peth, S., Smucker, A. (2006). Quantification of soil shrinkage in 2D by digital image processing of soil surface, Soil and Tillage Research, 91(1-2): 173-180.
  • Raschke, S. A., Hryciw R. D. (1997). Grain-size distribution of granular soils by computer vision, Geotechnical Testing Journal, 20(4): 433–442.
  • Ruzyla, K. (1984). Characterization of pore space by quantitative image analysis, 59th annual technical conference and exhibition, Society of petroleum engineers of AIME, (SPE paper 13133), Houston-TX.
  • Tang, C., Shi, B., Liu, C., Zhao, L., Wang, B. (2208). Influencing factors of geometrical structure of surface shrinkage cracks in clayey soils, Engineering Geology, 101(3-4): 204-217.
  • TS 699. Doğal yapı taşları - inceleme ve laboratuar deney yöntemleri, Türk Standardları Enstitüsü, Bakanlıklar, Ankara.
  • Vincent, L., Soille, P. (1991). Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal, 13: 583-9.
  • Young, I.T., Gerbrands, J.J., Viliet, L.J.V. (1998). Fundamentals of Image Processing, Delft University of Technology, ISBN 90–75691–01–7.

Görüntü Analizi Yöntemlerinin Geoteknik Mühendisliğinde Kullanımı

Yıl 2018, Cilt: 9 Sayı: 1, 33 - 44, 17.01.2018
https://doi.org/10.29048/makufebed.345053

Öz

Görüntü işleme teknolojisi; nesnelerin
görüntülerinin bilgisayar ortamına aktarılması ve belirlenen amaç doğrultusunda
bilgisayar ile işlenmesini içerir. İnsan gözünün yapabileceği işleri taklit
etmeyi amaçlayan görüntü analizi ise günümüz mühendisleri ve bilim insanları
için en popüler konuların başında gelir. Son yıllarda artan bir hızla deformasyon
ölçümleri, kayma analizleri, boşluk analizleri, dane boyut ve biçim
parametrelerinin belirlenmesi, geotekstil özelliklerinin belirlenmesi gibi
çözümler için geoteknik mühendisliğinde de kullanılmaktadır. Bu çalışmada;
görüntü analiz yöntemlerinin geoteknik mühendisliğinde karşılaşılan
problemlerin çözümüne dönük kullanımı araştırılmıştır. Laboratuvarda ve arazide
geo-malzemelerin tanımlanmasında ve mekanik davranışın ortaya konması sırasında
destekleyici yöntem olarak görüntü analizlerinin kullanımı konularındaki
literatür değerlendirilmiş, yöntemin avantaj ve limitleri tartışılmıştır.

Kaynakça

  • Al-Harthi, A.A., Al-Amri, R.M., Shehata, W.M. (1999). The porosity and engineering properties of vesicular basalt in Saudi Arabia. Engineering Geology, 54: 313– 320.
  • Al-Rousan T. M. (2004). Characterizatıon of aggregate shape properties usıng a computer automated system, Doctor of Philosophy, Texas A&M University, Civil Engineering, 211, Texas.
  • Alshibli, K. A., Al-Hamdan, M. Z. (2001). Estimating volume change of triaxial soil specimens from planar images, Computer-Aided Civil and Infrastructure Engineering, 16(6): 415-421.
  • Alshibli, K.A., Alsaleh, M.I. (2004). Characterizing surface roughness and shape of sands using digital microscopy, Journal of Computing in Civil Engineering, 18 (1): 36-45.
  • Alshibli, K.A., Batiste, S.N., Sture, S. (2003). Strain localization in sand: plane strain versus triaxial compression, Journal of Geotechnical and Geoenvorimental Engineering, ASCE, 129(6): 483-494.
  • Alshibli, K. A., Sture, S. (2000) Shear Band Formation in Plane Strain Experiments of Sand, ASCE, Journal of Geotechnical & Geoenvironmental Engineering, 126(6), 495-503.
  • ASTM C97, Standard Test Methods for Absorption and Bulk Specific Gravity of Dimension Stone, ASTM Standards, ASTM International, Philadelphia, USA.
  • ASTM D 427-83, Standard test method for shrinkage factors of soil, ASTM Standards, ASTM International, Philadelphia, USA.
  • ASTM D 4943-02, Standard Test Method for Shrinkage Factors of Soils by the Wax Method, ASTM Standards, ASTM International, Philadelphia, USA.
  • Aydilek, A.H. (2006). A semi-analytical model for development of woven geotextile filter selection criteria. Geosynthetics International, 13(2): 59–72.
  • Aydilek, A.H. Edil, T.B. (2004). Evaluation of Woven Geotextile Pore Structure Parameters Using Image Analysis, Geotechnical Testing Journal, 27(1): 1-12.
  • Aydilek, A.H., Kutay, M.E., Sparacino, R., Dafla, H. (2007). Image Analysis for QC/QA of Geosynthetic Deformation during Wide Width Tensile Testing, Proceedings of Geosynthetics 2007, Washington, D.C.
  • Aydilek, A.H., Oguz, S.H., Edil, T.B. (2005). Constriction size of geotextile filters. Journal of Geotechnical and Geoenvironmental Engineering, ASCE 131(1): 28–38.
  • Baxes, G.A. (1994). Digital image processing, principles and applications. 452 s., John Wiley & Sons, Inc., USA.
  • Beucher, S., Lantuejoul, C. (1979). Use of watersheds in contour detection. In the Proceedings of the international Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, Rennes, France.
  • Bhatia, S., Soliman, A. (1990). Frequency distribution of void ratio of granular materials determined by an image analyzer, Soils and Foundations, 30(1): 1-16.
  • Brzezicki, J. ve Kasperkiewicz, J. (1999). Automatic image analysis in evaluation of aggregate shape, Journal of Computing in Civil Engineering, 13(2), 123-128.
  • Castelman, R. K. (1996). Digital image processing. Prentice hall, Englewood Cliffs, New Jersey, USA.
  • Cheng, Y.P., White, D.J., Bowman, E.T., Bolton, M.D., Soga, K. (2001). The observation of soil microstructure under load, 4th International Conference on Micromechanics of Granular Media-Powders & Grains 2001, Kishino Y. (Ed): 69-72.
  • Crabtree, S.J., Ehrlich, Jr.R., Prince, C. (1984). Evaluation of strategies for segmentations of reservoir rocks, Computers Vision, Graphics and Image Processing, 28(1): 1-18.
  • Dipova N. (2014). Digital Image Analysis Based Porosity Measurement On Macro-Porous Rocks, V. Global Stone Congress, Antalya, 22-25 Ekim 2014, pp.70-70
  • Dipova, N. (2017a). Determining the grain size distribution of granular soils using image analysis, Acta Geotechnica Slovenica, 14: 28-37.
  • Dipova, N. (2017b). Görüntü analizi tekniklerinin serbest basınç dayanımı deneyinde kullanımı, 7. Geoteknik Sempozyumu 22-23-24 Kasım 2017, İstanbul.
  • Erhardt, A. (2000). Theory and Applications of Digital Image Processing, University of Applied Sciences, 54p.
  • Freilich, B., Zornberg, J.G. (2010). A Model for the Characterization of Scrap the Scrap Tire Bale Interface, Proceedings of the GeoFlorida 2010 Conference (GSP 199), Geo-Institute, ASCE, February 20-24, p. 2933-2942.
  • Frost, J.D., Jang, D.-J. (2000). Evolution of sand microstructure during shear. ASCE Jorurnal of Geotechnical and Geoenvironmental Engineering, 126(2): 116-130.
  • Ghalib, A.M., Hryciw, R.D. (1999). Soil partical size distribution by mosaic imaging and watershed analysis, Journal of Computing in Civil Engineering,13(2): 80-87.
  • Goodman, R. E., Ahlgren, C. S. (2000). Evaluating safety of concrete gravity dam on weak rock: Scott Dam, Journal of Geotechnical and Geoenvironmental Engineering, 126(5): 429–442.
  • Gonzalez, R. F., Woods R. E. (2001). Digital Image Processing, Prentice Hall, USA.
  • Güler, M., Edil, T.B., Bosscher P.J. (1999). Measurement of particle movement in granular soils using image analysis, ASCE Journal of Computing in Civil Engineering, 13 (2): 116-122.
  • Haneberg, W.C. (2004). Simulation of 3-D block populations to characterize outcrop sampling bias in block-in-matrix rocks (bimrocks), Felsbau-Rock and Soil Engineering, 22: 19–26.
  • Hryciw R.D., Raschke S.A. (1996). Development of a computer vision technique for insitu soil chracterization, Transportation Research Record, 1526: 86-97.
  • Hyoungkwan K., Haas, K.T., Rauch, A.F., Browne, C. (2003). 3D image segmentation of aggregates from laser profiling, Computer-Aided Civil and Infrastructure Engineering, 18: 254-263.
  • Hu, R.L., Yue, Z.Q., Tham, L.G., Wang, L.C. (2005). Digital image analysis of dynamic compaction effects on clay fills, ASCE Journal of Geotechnical and Geoenvironmental Engineering,131(11):1411-1422.
  • Kahraman, S., Alber, M., Fener, M., Gunaydin, O. (2010). The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis, Expert Systems with Applications, 37: 8750–8756.
  • King, R.P. (1984). Measurement of particle size distribution by image analyser, Powder Technology, 39(2): 279-289.
  • Kuo, C.Y., Frost, J.D. (1996). Uniformity evaluation of cohesionless specimens using digital image analysis. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 122(5), 390–396.
  • Kwan, A.K.H., Mora, C.F. Chan, H.C. (1999). Particle shape analysis of coarseaggregate using digital image processing, Cement and Concrete Research. 29(9): 1403-1410.
  • Macari, E. M., Parker, J. K., Costes, N. C. (1997). Measurement of volume changes in triaxial tests using digital imaging tecniques, Geotecnical Testing Journal, 20(1): 103-109.
  • Medley, E. W. (2002). Estimating block size distribution of melanges and similar block-in-matrix rocks (bimrocks). In R. Hammah, W. Bawden, J. Curran, & M. Telesnicki (Eds.), Proceedings of the 5th North American rock mechanics symposium (pp. 509–516). Toronto, Canada: University of Toronto Press.
  • Mertens, G., Elsen, J. (2006). Use of computer assisted image analysis for the determination of the grain-size distribution of sands used in mortars, Cement and Concrete Research, 36: 1453-1459.
  • Mora, C.F., Kwan, A.K.H., Chan, H.C. (1998). Particle size distribution analysis of coarse aggregate using digital image processing, Cement and Concrete Research, 28(6), 921-932.
  • Mora, C.F., Kwan, A.K.H. (2000). Sphericity, Shape Factor, and Convexity Measurement of Coarse Aggregate for Concrete Using Digital Image Processing, Cement and Concrete Research 30 (3): 351-358.
  • Muhunthan, B., Masad, E., Asaad, A. (2000). Measurement of uniformity and anisotropy in granular materials, Geotechncal Testing Journal, 23(4), 423-431.
  • Nielsen, B.D. (2004). Non-Destructive soil testing using X-ray Computed Tomography, M.S. Thesis, Montana State University, Bozeman, Montana.
  • Ören, A. H., Önal, O., Özden, G., Kaya, A. (2006). Nondestructive evaluation of volumetric shrinkage of compacted mixtures using digital image analysis, Engineering Geology, 85(3-4), 239-250.
  • Peng, X., Horn, R., Peth, S., Smucker, A. (2006). Quantification of soil shrinkage in 2D by digital image processing of soil surface, Soil and Tillage Research, 91(1-2): 173-180.
  • Raschke, S. A., Hryciw R. D. (1997). Grain-size distribution of granular soils by computer vision, Geotechnical Testing Journal, 20(4): 433–442.
  • Ruzyla, K. (1984). Characterization of pore space by quantitative image analysis, 59th annual technical conference and exhibition, Society of petroleum engineers of AIME, (SPE paper 13133), Houston-TX.
  • Tang, C., Shi, B., Liu, C., Zhao, L., Wang, B. (2208). Influencing factors of geometrical structure of surface shrinkage cracks in clayey soils, Engineering Geology, 101(3-4): 204-217.
  • TS 699. Doğal yapı taşları - inceleme ve laboratuar deney yöntemleri, Türk Standardları Enstitüsü, Bakanlıklar, Ankara.
  • Vincent, L., Soille, P. (1991). Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal, 13: 583-9.
  • Young, I.T., Gerbrands, J.J., Viliet, L.J.V. (1998). Fundamentals of Image Processing, Delft University of Technology, ISBN 90–75691–01–7.
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Derleme Makale
Yazarlar

Nihat Dipova

Yayımlanma Tarihi 17 Ocak 2018
Kabul Tarihi 16 Ocak 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 9 Sayı: 1

Kaynak Göster

APA Dipova, N. (2018). Görüntü Analizi Yöntemlerinin Geoteknik Mühendisliğinde Kullanımı. Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 9(1), 33-44. https://doi.org/10.29048/makufebed.345053