Journal of Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회논문집)

Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회)
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Smartphone Digital Image Processing Method for Sand Particle Size Analysis

모래 입도분석을 위한 스마트폰 디지털 이미지 처리 방법

  • Ju-Yeong Hur (School of Spatial Environment System Engineering, Handong Global University) ;
  • Se-Hyeon Cheon (School of Spatial Environment System Engineering, Handong Global University)
  • 허주영 (한동대학교 공간환경시스템공학부) ;
  • 천세현 (한동대학교 공간환경시스템공학부)
  • Received : 2023.11.24
  • Accepted : 2023.12.26
  • Published : 2023.12.31
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Abstract

The grain size distribution of sand provides crucial information for understanding coastal erosion and sediment deposition. The commonly used sieve analysis for grain size distribution analysis has limitations such as time-consuming processes and the inability to obtain information about individual particle shapes and colors. In this study, we propose a grain size distribution analysis method using smartphone digital images, which is simpler and more efficient than the sieve analysis method. During the image analysis process, we effectively detect particles from relatively low-resolution smartphone digital images by extracting particle boundaries through image gradient calculation. Using samples collected from four beaches in Gyeongsangbuk-do, we compare and validate the proposed boundary extraction image analysis method with the analysis method that does not extract boundaries, against sieve analysis results. The proposed method shows an average error rate of 8.21% at D50, exhibiting a 65% lower error compared to the method without boundary extraction. Therefore, grain size distribution analysis using smartphone digital images is convenient, efficient, and demonstrated accuracy comparable to sieve analysis.

백사장 모래의 입도분포는 해빈의 침식과 퇴적을 파악하는 데 중요한 정보를 제공한다. 모래의 입도분포 분석에 보편적으로 사용되는 체가름시험은 분석 시간이 길고 개별 입자의 형상과 색에 대한 정보를 얻을 수 없다는 한계점이 있다. 본 연구에서는 체가름시험법 보다 측정 과정이 간편하고 효율적인 스마트폰 디지털 이미지를 이용한 입도분포 분석 방법을 제안하였다. 이미지 분석 과정 중 이미지 기울기(Image Gradient) 계산을 통한 입자 경계 추출로 해상도가 상대적으로 낮은 스마트폰 디지털 이미지의 배경으로부터 입자를 효과적으로 검출하였다. 경상북도 4곳의 해수욕장에서 채취한 시료를 이용해 본 연구에서 제안한 경계 추출 이미지 분석법과 경계를 추출하지 않는 분석법을 각각 체가름시험 결과와 비교 검증하였을 때, 본 연구에서 제안한 방식은 D50에서 평균 8.21%의 평균 오차율을 보여 경계를 추출하지 않는 분석법 보다 65% 낮은 오차를 보였다. 따라서 스마트폰 디지털 이미지를 이용한 입도분포 분석은 간편하고 효율적이며 체가름시험에 준하는 정확성을 가짐을 확인하였다.

Keywords

Acknowledgement

본 과제(결과물)는 교육부와 한국연구재단의 재원으로 지원을 받아 수행된 3단계 산학연협력 선도대학 육성사업(LINC3.0)의 연구 결과입니다. 연구에 사용된 이미지와 코드는 교신저자에 문의해 얻을 수 있습니다.

References

  1. An, P., Tang, H., Li, C., Fang, K., Lu, S. and Zhang, J. (2022). A fast and practical method for determining particle size and shape by using smartphone photogrammetry. Measurement: Journal of the International Measurement Confederation, 193. https://doi.org/10.1016/j.measurement.2022.110943.
  2. Bae, H., Do, K., Kim, I. and Chang, S. (2022). Proposal of parameter range that offered optimal performance in the coastal morphodynamic model (XBeach) through GLUE. Journal of Ocean Engineering and Technology, 36(4), 251-269. https://doi.org/10.26748/KSOE.2022.013
  3. Lim, C., Kim, T.-K., Kim, J.-B. amd Lee, J.-L. (2022). A study on the influence of sand median grain size on the short-term recovery process of shorelines. Frontiers in Marine Science, 9:906209.
  4. Cheon, S.-H., Ahn, K. and Suh, K.-D. (2013). Beach sand grain size analysis using commercial flat-bed scanner. Journal of Korean Society of Coastal and Ocean Engineers, 25(5), 301-310. https://doi.org/10.9765/KSCOE.2013.25.5.301.
  5. Dean, R.G. (1977). Equilibrium beach profiles: US Atlantic and Gulf coasts.
  6. Ferrer, B., Nostas, C. and Mas, D. (2021). Evaluation of a simple and affordable image-based procedure to measure particle size distribution. Geotechnical Testing Journal, 44(3). https://doi.org/10.1520/GTJ20190457.
  7. Fisher, P., Aumann, C., Chia, K., O'Halloran, N. and Chandra, S. (2017). Adequacy of laser diffraction for soil particle size analysis. PLOS ONE, 12(5), e0176510. https://doi.org/10.1371/JOURNAL.PONE.0176510.
  8. Gee, G.W. and Bauder, J.W. (1986). Particle-size analysis. Methods of Soil Analysis, Part 1 Physical and Mineralogical Methods, 383-411. https://doi.org/10.2136/SSSABOOKSER5.1.2ED.C15.
  9. Gibbs, R.J. (1974). A settling tube system for sand-size analysis. Journal of Sedimentary Research, 44(2), 583-588. https://doi.org/10.1306/74D72A9A-2B21-11D7-8648000102C1865D.
  10. Hayazi, F., Daud, M.E. and Mokhtar (2023). Beach volume changes and shoreline sediment properties at eroded area in batu pahat. Trends in Civil Engineering and Built Environment, 4(2), 219-231. https://doi.org/10.30880/rtcebe.2023.04.02.025.
  11. Jin, H., Do, K., Chang, S. and Kim, I.H. (2020). Field observation of morphological response to storm waves and sensitivity analysis of XBeach model at beach and crescentic bar. Journal of Korean Society of Coastal and Ocean Engineers, 32(6), 446-457 (in Korean). https://doi.org/10.9765/KSCOE.2020.32.6.446.
  12. Kim, K.H. and Widayati, A.Y.W. (2012). Study on alternatives of sand placement method for beach nourishment project. KSCE Journal of Civil Engineering, 16(4), 478-485. https://doi.org/10.1007/S12205-012-1432-9.
  13. McCall, R.T., Masselink, G., Poate, T G., Roelvink, J.A., Almeida, L.P., Davidson, M. and Russell, P.E. (2014). Modelling storm hydrodynamics on gravel beaches with XBeach-G. Coastal Engineering, 91, 231-250. https://doi.org/10.1016/j.coastaleng.2014.06.007
  14. Ohm, H.-S. and Hryciw, R.D. (2014). Size distribution of coarsegrained soil by sedimaging. Journal of Geotechnical and Geoenvironmental Engineering, 140(4), 04013053. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001075.
  15. Oliveira, J.N.C., Oliveira, F.S., Neves, M.G., Clavero, M. and Trigo-Teixeira, A.A. (2020). Modeling wave overtopping on a seawall with XBeach, IH2VOF, and Mase Formulas. Water 12(9), 2526.
  16. Oliveira Morais, P.A., de Souza, D.M., de Melo Carvalho, M.T., Madari, B.E. and de Oliveira, A.E. (2019). Predicting soil texture using image analysis. Microchemical Journal, 146, 455-463. https://doi.org/10.1016/J.MICROC.2019.01.009.
  17. Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1), 62-66. https://doi.org/10.1109/TSMC.1979.4310076
  18. Schluter, S. and Vogel, H.J. (2016). Analysis of soil structure turnover with garnet particles and X-Ray microtomography. PLOS ONE, 11(7), e0159948. https://doi.org/10.1371/JOURNAL.PONE.0159948
  19. Sobel, I. and Feldman, G. (1973). A 3?isotropic gradient operator for image processing. Pattern Classification and Scene Analysis. 271-272.
  20. Tafesse, S., Fernlund, J.M.R. and Bergholm, F. (2012). Digital sieving-Matlab based 3-D image analysis. Engineering Geology, 137-138, 74-84. https://doi.org/10.1016/J.ENGGEO.2012.04.001.
  21. Yu, K. and Cho, W. (2019). Analysis of size distribution of riverbed gravel through digital image processing. Journal of Korea Water Resources Association, 52(7), 493-503 (in Korean).