ASTM. (2017). Standard test method for particle-size distribution (gradation) of fine-grained soils using the sedimentation (hydrometer) analysis. In ASTM (Vol. 7928, pp. 1-25). DOI:
10.1520/D7928-21E01
Athanassiadis, A. G., Miskin, M. Z., Kaplan, P., Rodenberg, N., Lee, S. H., Merritt, J., Brown, E., Amend, J., Lipson, H., & Jaeger, H. M. (2014). Particle shape effects on the stress response of granular packings.
Soft Matter,
10(1), 48-59. DOI:
10.1039/C3SM52047A
Aydin, M., & Kurnaz, T. F. (2023). An alternative method for the particle size distribution: Image processing.
Turk. J. Eng.,
7(2), 108-115. DOI:
10.31127/tuje.1053462
Panagiotis Antoniadis. (2023). How to Convert an RGB Image to a Grayscale. Available online at:
https://www.baeldung.com, Accessed 19, June 2023.
Behringer, R. P., Howell, D., Kondic, L., Tennakoon, S., & Veje, C. (1999). Predictability and granular materials.
Physica D: Nonlinear Phenomena, 133(1-4), 1-17. DOI:
10.1016/S0167-2789(99)00094-9
Coates, G. F., & Hulse, C. A. (1985). A comparison of four methods of size analysis of fine-grained sediments.
New Zealand J. Geol. Geophys.,
28(2), 369-380. DOI:
10.1080/00288306.1985.10422234
Damadipour, M., Nazarpour, M., & Alami, M. T. (2019). Evaluation of particle size distribution using an efficient approach based on image processing techniques.
Iran. J. Sci. Technol. Trans. Civil Eng., 43, 429-441. DOI:
10.1007/s40996-018-0175-3
Dan, H. C., Bai, G. W., & Zhu, Z. H. (2021). Application of deep learning-based image recognition technology to asphalt–aggregate mixtures: Methodology.
Construct. Build. Mater., 297, 123770. DOI:
10.1016/j.conbuildmat.2021.123770
El-Yamany, I., Wael, A., Adly, N., & Torki, M. (2023, June). STACKMAPS: A Visualization Technique for Diabetic Retinopathy Grading.
In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE. DOI:
10.1109/ICASSP49357.2023.10095667
Garcia, X., Akanji, L. T., Blunt, M. J., Matthai, S. K., & Latham, J. P. (2009). Numerical study of the effects of particle shape and polydispersity on permeability.
Phys. Rev. E, 80(2), 021304. DOI:
10.1103/PhysRevE.80.021304
Jana, B. R., Thotakura, H., Baliyan, A., Sankararao, M., Deshmukh, R. G., & Karanam, S. R. (2023). Pixel density based trimmed median filter for removal of noise from surface image.
Appl. Nanosci., 13(2), 1017-1028. DOI:
10.1007/s13204-021-01950-0
Johndcook .(2009). Three algorithms for converting color to grayscale. Avalibale online at:
https://www.johndcook.com, Accessed 24, August 2019.
Kalidhas, M., & Sivakumar, R. (2022). Image processing and Supervised Classification of LANDSAT data for Flood Impact Assessment on Land Use and Land Cover. In 2022 2
nd International Conference on Technological Advancements in Computational Sciences (ICTACS) (pp. 437-440). IEEE. DOI:
10.1109/ICTACS56270.2022.9988164
Kim, D., Song, J., & Park, J. (2023). Quantifying Soil Particle Settlement Characteristics through Machine Vision Analysis Utilizing an RGB Camera.
Agri., 13(9), 1674. DOI:
10.3390/agriculture13091674
Kumar, K., Mishra, R. K., & Nandan, D. (2020). Efficient hardware of RGB to Gray conversion realized on FPGA and ASIC.
Procedia Comput. Sci., 171, 2008-2015. DOI:
10.1016/j.procs.2020.04.215
Liu, J., Cheng, D., Li, Y., Zhao, K., & Kou, Q. (2022). Quantitative evaluation of the influence of coal particle size distribution on gas diffusion coefficient by image processing method.
Fuel, 314, 122946. DOI:
10.1016/j.fuel.2021.122946
Mora, C. F., Kwan, A. K. H., & Chan, H. C. (1998). Particle size distribution analysis of coarse aggregate using digital image processing.
Cement Concrete Res., 28(6), 921-932. DOI:
10.1016/S0008-8846(98)00043-X
Otsu, N. (1979). A threshold selection method from gray-level histograms.
IEEE Trans. Syst. Man Cybernet., 9(1), 62-66. DOI:
0018-9472/79/0100-0062$00.75
Sagayaraj, A. S., Kabilesh, S. K., Mohanapriya, D., & Anandkumar, A. (2021). Determination of soil moisture content using image processing-a survey. 2021 6
th International Conference on Inventive Computation Technologies (ICICT) (pp. 1101-1106). IEEE. DOI:
10.1109/ICICT50816.2021.9358736
Santos, R., & Fernandes, J. N. (2022). Estimation of river flow discharges using image processing. International Conference on Testing and Experimentation in Civil Engineering (pp. 363-374).
Cham: Springer Nature Switzerland. DOI:
10.1007/978-3-031-29191-3_30
Shinohara, K., Oida, M., & Golman, B. (2000). Effect of particle shape on angle of internal friction by triaxial compression test.
Powder Technol., 107(1-2), 131-136. DOI:
10.1016/S0032-5910(99)00179-5
Soille, P., Pesaresi, M., & Ouzounis, G. K. (2011). Mathematical morphology and its applications to image and signal processing. 10
th International Symposium, ISMM 2011, Verbania-Intra, Italy, July 6-8, 2011,
Proceedings. DOI
: 10.1007/978-3-642-21569-8
Soille, P., & Soille, P. (2004). Opening and closing. Morphological image analysis:
Principl. Appl., 105-137. DOI:
10.1007/978-3-662-05088-0_4
Soille, P., & Soille, P. (2004). Hit-or-miss and skeletons: In Morphological Image Analysis:
Principl. Appl., 139-182. DOI:
10.1007/978-3-662-05088-0_5
Sun, Q., Zheng, J., Coop, M. R., & Altuhafi, F. N. (2019). Minimum image quality for reliable optical characterizations of soil particle shapes.
Comput. Geotech., 114, 103110. DOI:
10.1016/j.compgeo.2019.103110
Sun, X. (2021). Design of the poster image system based on human vision.
Sci. Program., 2021, 1-14. DOI:
10.1155/2021/1411145
Tuan, N. M., Kim, Y., Lee, J. Y., & Chin, S. (2022). Automatic stereo vision-based inspection system for particle shape analysis of coarse aggregates.
J. Comput. Civil Eng.,
36(2), 04021034. DOI:
10.1061/(ASCE)CP.1943-5487.0001005
Waris, M. I., Mir, J., Plevris, V., & Ahmad, A. (2020). Predicting compressive strength of CRM samples using Image processing and ANN. In IOP Conference Series: Materials Science and Engineering (Vol. 899, No. 1, p. 012014). IOP Publishing. DOI:
10.1088/1757-899X/899/1/012014
Xu, Z., Zhang, X., Chen, L., Pei, K., & Xu, B. (2016). Python probabilistic type inference with natural language support. In
Proceedings of the 2016 24th ACM SIGSOFT international symposium on foundations of software engineering (pp. 607-618). DOI:
10.1145/2950290.2950343
Yang, J., & Luo, X. D. (2015). Exploring the relationship between critical state and particle shape for granular materials.
J. Mechanic. Phys. Solid., 84, 196-213. DOI:
10.1016/j.jmps.2015.08.001
Yu, L., He, S., Liu, X., Jiang, S., & Xiang, S. (2022). Intelligent crack detection and quantification in the concrete bridge: A deep learning-assisted image processing approach.
Adv. Civil Eng., 2022. DOI:
10.1155/2022/1813821
)