Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido

ilustraciones, diagramas

Autores:: Gómez Mateus, José Alfredo

Tipo de recurso:

Fecha de publicación:: 2023

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

id	UNACIONAL2_0f4277866cea94d0bab9056f1815fdcb
oai_identifier_str	oai:repositorio.unal.edu.co:unal/86160
network_acronym_str	UNACIONAL2
network_name_str	Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
dc.title.translated.eng.fl_str_mv	Determination of roughness from images obtained with a Scanning Electron Microscope
title	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
spellingShingle	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido 000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computación 620 - Ingeniería y operaciones afines::621 - Física aplicada Rugosidad Microscopio Electrónico de Barrido Reconstrucción en 3D Nubes de puntos Algoritmos de detección de puntos característicos Dimensión fractal Roughness Scanning Electron Microscopy 3D reconstruction Point clouds Fractal dimension Characteristic point detection algorithms Rugosidad (electrónica) microscopio electrónico dimensión fractal algoritmo electron microscope fractal dimension algorithm
title_short	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
title_full	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
title_fullStr	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
title_full_unstemmed	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
title_sort	Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido
dc.creator.fl_str_mv	Gómez Mateus, José Alfredo
dc.contributor.advisor.spa.fl_str_mv	Sandino del Busto, John William
dc.contributor.author.spa.fl_str_mv	Gómez Mateus, José Alfredo
dc.contributor.researchgroup.spa.fl_str_mv	Microscopía Electrónica
dc.subject.ddc.spa.fl_str_mv	000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computación 620 - Ingeniería y operaciones afines::621 - Física aplicada
topic	000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computación 620 - Ingeniería y operaciones afines::621 - Física aplicada Rugosidad Microscopio Electrónico de Barrido Reconstrucción en 3D Nubes de puntos Algoritmos de detección de puntos característicos Dimensión fractal Roughness Scanning Electron Microscopy 3D reconstruction Point clouds Fractal dimension Characteristic point detection algorithms Rugosidad (electrónica) microscopio electrónico dimensión fractal algoritmo electron microscope fractal dimension algorithm
dc.subject.proposal.spa.fl_str_mv	Rugosidad Microscopio Electrónico de Barrido Reconstrucción en 3D Nubes de puntos Algoritmos de detección de puntos característicos Dimensión fractal
dc.subject.proposal.eng.fl_str_mv	Roughness Scanning Electron Microscopy 3D reconstruction Point clouds Fractal dimension Characteristic point detection algorithms
dc.subject.wikidata.spa.fl_str_mv	Rugosidad (electrónica) microscopio electrónico dimensión fractal algoritmo
dc.subject.wikidata.eng.fl_str_mv	electron microscope fractal dimension algorithm
description	ilustraciones, diagramas
publishDate	2023
dc.date.issued.none.fl_str_mv	2023
dc.date.accessioned.none.fl_str_mv	2024-05-24T20:58:20Z
dc.date.available.none.fl_str_mv	2024-05-24T20:58:20Z
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/86160
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/86160 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Akhtar, K., Khan, S. A., Khan, S. B. K., & Asiri, A. M. (2018). Scanning Electron Microscopy: Principle and Applications in Nanomaterials Characterization. Springer. https://doi.org/10.1007/978-3-319-92955-2 4 Alcantarilla, P. F., Bartoli, A., & Davison, A. J. (2012). KAZE Features. Eur. Conf. on Computer Vision (ECCV) Arasan, S., Akbulut, S., & Hasiloglu, A. S. (2011). The relationship between the fractal dimension and shape properties of particles. KSCE Journal of Civil Engineering, 15 (7), 1219-1225. https://doi.org/10.1007/s12205-011-1310-x Barash, D., Israeli, M., & Kimmel, R. (2001). An Accurate Operator Splitting Scheme for Nonlinear Diffusion Filtering. En M. Kerckhove (Ed.), Scale-Space and Morphology in Computer Vision (pp. 281-289, Vol. 2106). Springer. https://doi.org/10.1007/3- 540-47778-0 25 Bernardini, F., Mittleman, J., Rushmeier, H., Silva, C., & Taubin, G. (1999). The ballpivoting algorithm for surface reconstruction. IEEE Transactions on Visualization and Computer Graphics, 5 (4), 349-359 Blachowski, A., & Ruebenbauer, K. (2009). Roughness method to estimate fractal dimension. Acta Physica Polonica A, 115 (3), 636-640 Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 327 (8476), 307-310. https://doi.org/ 10.1016/S0140-6736(86)90837-8 Bonetto, R. D., Ladaga, J. L., & Ponz, E. (2006). Measuring Surface Topography by Scanning Electron Microscopy. II. Analysis of Three Estimators of Surface Roughness in Second Dimension and Third Dimension. Microscopy and Microanalysis, 12, 178-186 Botsch, M., Kobbelt, L., Pauly, M., Alliez, P., & L´evy, B. (2010). Polygon Mesh Processing. A K Peters/CRC Press Bradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer vision with the OpenCV library. O’Reilly Media, Inc Brown, M., & Lowe, D. G. (2002). Invariant features from interest point groups. British Machine Vision Conference Calonder, M., Lepetit, V., Strecha, C., & Fua, P. (2010). BRIEF: Binary Robust Independent Elementary Features. European conference on computer vision, 778-792 Chongpu, Z., Hanaor, D., Proust, G., & Gan, Y. (2017). Stress-Dependent Electrical Contact Resistance at Fractal Rough Surfaces. Journal of Engineering Mechanics, 143 (3), B4015001. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000967 Datatab. (2021). Tutorial: Kendall’s Tau. Consultado el 8 de diciembre de 2023, desde https: //datatab.es/tutorial/kendalls-tau Dektak 150 Profiler User’s Manual [Available from Veeco Instruments Inc., (www.veeco.com)]. (2007). Veeco Instruments Inc. Plainview, NY. Edelsbrunner, H., Kirkpatrick, D. G., & Seidel, R. (1983). On the shape of a set of points in the plane. IEEE Transactions on Information Theory, 29 (4), 551-559. Elcometer. (2022). Rugosímetro MarSurf PS1 Elcometer 7061 [ Último acceso: 2023-04-04]. http ://www.elcometer .com/es/inspeccin - revestimientos/limpieza- de- superficie - perfil - de - la - superficie / rugosidad - de - la - superficie / rugosimetro - marsurf - ps1 - elcometer-7061.html El-Gomati, M. M., Wells, T., Zha, X., Sykes, R., Russo, C. J., Henderson, R., & McMullan, G. (2021). 100 keV vacuum sealed field emission gun for high resolution electron microscopy. Journal of Vacuum Science & Technology B, 39 (6), 062804. https://doi. org/10.1116/6.0001275 Forum, O. Q. (2013, agosto). Is SURF algorithm used in OPENCV patented? https : / / answers.opencv.org/question/18259/is-surf-algorithm-used-in-opencv-patented/ Forum, O. Q. (2020, noviembre). Expired US patent on SIFT. https://answers.opencv.org/ question/238447/expired-us-patent-on-sift/ Gadelmawla, E., Koura, M., Maksoud, T., Elewa, I., & Soliman, H. (2002). Roughness parameters. Journal of Materials Processing Technology, 123 (1), 133-145. https://doi. org/https://doi.org/10.1016/S0924-0136(02)00060-2 Goldstein, J. I., Newbury, D. E., Joy, D. C., Lyman, C. E., Echlin, P., Lifshin, E., Sawyer, L., & Michael, J. R. (2003). Scanning Electron Microscopy and X-Ray Microanalysis. Springer. Gontard, L., L´opez-Castro, J., Gonz´alez-Rovira, L., V´azquez-Mart´ınez, J., Varela-Feria, F., Marcos, M., & Calvino, J. (2017). Assessment of engineered surfaces roughness by high-resolution 3D SEM photogrammetry. Ultramicroscopy, 177, 106-114. https:// doi.org/https://doi.org/10.1016/j.ultramic.2017.03.007 Hanaor, D., Gan, Y., & Einav, I. (2016). Static friction at fractal interfaces. Tribology International, 93, 229-238. https://doi.org/10.1016/j.triboint.2015.09.016 Hartley, R., & Zisserman, A. (2003). Multiple View Geometry in Computer Vision. Cambridge University Press Henao-Londoño, J. C., Riaño-Rojas, J. C., Gómez-Mendoza, J. B., & Restrepo-Parra, E. (2018). 3D Stereo Reconstruction of SEM Images. Modern Applied Science, 12 (12), 57. https://doi.org/10.5539/mas.v12n12p57 Kalvani, P. R., Jahangiri, A. R., Shapouri, S., Sari, A., & Jalili, Y. S. (2019). Multimode AFM analysis of aluminum-doped zinc oxide thin films sputtered under various substrate temperatures for optoelectronic applications. Superlattices and Microstructures, 132, 106173. https://doi.org/10.1016/j.spmi.2019.106173 Kayaalp, A., Rao, A. R., & Jain, R. (1990). Scanning Electron Microscope-Based Stereo Analysis. Machine Vision and Applications, 3, 231-246. Kazhdan, M., Bolitho, M., & Hoppe, H. (2006). Poisson surface reconstruction. Proceedings of the fourth Eurographics symposium on Geometry processing, 7. Koga, D., Kusumi, S., Shibata, H., & Watanabe, M. (2021). Applications of Scanning Electron Microscopy Using Secondary and Backscattered Electron Signals in Neural Structure. Frontiers in Neuroanatomy, 15. https://doi.org/10.3389/fnana.2021.647428 Li, Y., Shum, H.-Y., Tang, C.-K., & Szeliski, R. (2004). Stereo reconstruction from multiperspective panoramas. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26 (1), 45-62. https://doi.org/10.1109/TPAMI.2004.1261078 Lin Chen, F. R., & Heipke, C. (2021). Feature detection and description for image matching: from hand-crafted design to deep learning. Geo-spatial Information Science, 24 (1), 58-74. https://doi.org/10.1080/10095020.2020.1843376 Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30 (2), 77-116 Liu, Z., Wang, Y., Chen, J., Li, X., & Zhang, Z. (2019). Anisotropy of surface roughness of metals. Applied Surface Science, 479, 796-805. https://doi.org/10.1016/j.apsusc. 2019.02.163 Lowe, D. G. (1999). Object recognition from local scale-invariant features. Proceedings of the seventh IEEE international conference on computer vision, 2, 1150-1157. Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60 (2), 91-110. Luo, W., Schwing, A. G., & Urtasun, R. (2016). Efficient Deep Learning for Stereo Matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 5695-5703. Ma, Z., & Liu, S. (2018). A review of 3D reconstruction techniques in civil engineering and their applications. Advanced Engineering Informatics, 37, 163-174. https://doi.org/ https://doi.org/10.1016/j.aei.2018.05.005 Majumdar, A., & Bhushan, B. (1990). Fractal Characterization and Simulation of Rough Surfaces. American Society of Mechanical Engineers Mandelbrot, B. (1983). The Fractal Geometry of Nature. Henry Holt; Company. https:// books.google.com.co/books?id=0R2LkE3N7-oC Mate, C. M. (2008). Tribology on the Small Scale: Mesoscopic Physics and Nanotechnology. Oxford University Press Milanese, E., Brink, T., Aghababaei, R., & Molinari, J.-F. (2019). Emergence of self-affine surfaces during adhesive wear. Nature Communications, 10 (1), 1116. https://doi. org/10.1038/s41467-019-09127-8 Minitab. (2021). Estadísticos y gráficas para t de 1 muestra. Consultado el 8 de diciembre de 2023, desde https://support.minitab.com/es-mx/minitab/21/help-and-howto/ statistics/basic-statistics/how-to/1-sample-t/interpret-the-results/all-statisticsand- graphs/ Moeslund, T. B. (2012). BLOB Analysis. En Introduction to Video and Image Processing: Building Real Systems and Applications (pp. 103-115). Springer London. https://doi. org/10.1007/978-1-4471-2503-7 7 Montakhabi, F., Poursaeidi, E., Rahimi, J., & Sigaroodi, M. R. J. (2022). Investigation of the effect of BC layer surface roughness and TC layer porosity on stress values in plasma sprayed coatings based on SEM images. Materials Today Communications, 33, 104737. https://doi.org/https://doi.org/10.1016/j.mtcomm.2022.104737 Moons, T., Van Gool, L., & Vergauwen, M. (2009). 3D Reconstruction from Multiple Images: Part 1 - Principles. Foundations and Trends in Computer Graphics and Vision, 4, 287-404 Nayak, S. R., Mishra, J., & Palai, G. (2019). Analysing roughness of surface through fractal dimension: A review. Image and Vision Computing, 89, 21-34. https://doi.org/https: //doi.org/10.1016/j.imavis.2019.06.015 Odling, N. E. (1994). Natural fracture profiles, fractal dimension and joint roughness coefficients. Rock Mechanics and Rock Engineering, 27 (3), 135-153. https://doi.org/10. 1007/BF01020307 Oho, E. (2002). Digital image-processing technology useful for scanning electron microscopy and its practical applications. En P. W. Hawkes (Ed.), Electron Microscopy and Holography II (pp. 251-IV, Vol. 122). Elsevier. https://doi.org/https://doi.org/10. 1016/S1076-5670(02)80054-4 Oliveira, S. M. (2005). Analysis of Surface Roughness and Models of Mechanical Contacts [Tesis de grado]. Universita di Pisa Open3D. (2023). Surface Reconstruction. http://www.open3d.org/docs/release/tutorial/ geometry/surface reconstruction.html OpenCV. (2021). Understanding Features [Consultado el 15 de Octubre de 2022]. https : //docs.opencv.org/3.4/df/d54/tutorial py features meaning.html Parker, K. A., Ribet, S., Kimmel, B. R., dos Reis, R., Mrksich, M., & Dravid, V. P. (2022). Scanning Transmission Electron Microscopy in a Scanning Electron Microscope for the High-Throughput Imaging of Biological Assemblies. Biomacromolecules, 23 (8), 3235-3242. https://doi.org/https://doi.org/10.1021/acs.biomac.2c00323 Parsons, D. F., Walsh, R. B., & Craig, V. S. J. (2014). Surface forces: Surface roughness in theory and experiment. Journal of Chemical Physics, 140 (16), 164701. https://doi. org/10.1063/1.4871412 Perona, P., & Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (7), 629-639. Pfeifer, P. (1988). Fractals in Surface Science: Scattering and Thermodynamics of Adsorbed Films. En R. Vanselow & R. Howe (Eds.), Chemistry and Physics of Solid Surfaces VII (pp. 283-305, Vol. 10). Springer Berlin Heidelberg. https://doi.org/10.1007/978- 3-642-73902-6 10 Quan, L. (2010). Image-based modeling. Springer Science & Business Media. QuestionPro. (2020). Coeficiente de correlación de Spearman: ¿Qué es y cómo se calcula? Consultado el 8 de diciembre de 2023, desde https://www.questionpro.com/blog/es/ coeficiente-de-correlacion-de-spearman/ Reimer, L. (1998). Scanning Electron Microscopy: Physics of Image Formation and Microanalysis. Springer. Rivera, M. H., & Melo, M. E. R. (2001). La rugosidad de las superficies: Topometría. Ingenierías, 4, 27-33. Rosin, P. L. (1999). Measuring corner properties. Computer Vision and Image Understanding, 73 (2), 291-307. Rosten, E., & Drummond, T. (2006). Machine learning for high-speed corner detection. European conference on computer vision, 430-443. Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011). ORB: an efficient alternative to SIFT or SURF. in Proc. of the IEEE International Conf. on Computer Vision (ICCV). Sarode, V. (2022). What Are Point Clouds? https://medium.com/analytics-vidhya/whatare- point-clouds-3655d565e142 Sato, H., O-Hori, M., & Nakayama, K. (1982). Surface Roughness Measurement by Scanning Electron Microscope. CIRP Annals, 31 (1), 457-462. https://doi.org/https://doi.org/ 10.1016/S0007-8506(07)63347-2 Shet, V., & Picard, R. W. (2005). Python for scientific computing. Computing in Science & Engineering, 7 (3), 10-20 Sun, T., Li, Y., Liu, Y., Deng, B., Liao, C., & Zhu, Y. (2023). Advanced scanning electron microscopy and microanalysis: Applications to nanomaterials. En Y. Yin, Y. Lu & Y. Xia (Eds.), Encyclopedia of Nanomaterials (First Edition) (First Edition, pp. 183-209). Elsevier. https://doi.org/https://doi.org/10.1016/B978-0-12-822425-0.00104-4 Team, O. (2023). Feature Detection and Description. https://docs.opencv.org/4.x/d5/d51/ group features2d main.html TESCAN a.s. (2014). Scanning Electron Microscope: Instructions for Use. TESCAN. https: //www.csuchico.edu/sem/ assets/documents/vega-manual-2014.pdf Thäle, C., & Freiberg, U. (2008). A Markov Chain Algorithm for Determining Crossing Times Through Nested Graphs. Discrete Mathematics & Theoretical Computer Science. Töberg, S., & Reithmeier, E. (2020). Quantitative 3D Reconstruction from Scanning Electron Microscope Images Based on Affine Camera Models. Sensors, 20 (12), 3598. https: //doi.org/10.3390/s20123598 Vanderbilt University. (s.f.). The Hausdorff Dimension Viper, Q. (2022). Making Fractal Shapes with Python Wang, J., Wu, Y., Cao, Y., et al. (2020). Influence of surface roughness on contact angle hysteresis and spreading work. Colloid and Polymer Science, 298, 1107-1112. https: //doi.org/10.1007/s00396-020-04680-x Wang, Y., Liu, R., Ji, H., Li, S., Yu, L., & Feng, X. (2022). Correlating mechanical properties to fractal dimensions of shales under uniaxial compression tests. Environmental Earth Sciences, 82 (1), 2. https://doi.org/10.1007/s12665-022-10642-z Weickert, J., Ishikawa, S., & Imiya, A. (1999). Linear scale-space has first been proposed in Japan. Journal of Mathematical Imaging and Vision, 10. Weisstein, E. W. (2023). Menger Sponge Whitehouse, D. J. (2010). Surfaces and their Measurement. Butterworth-Heinemann. https: //www.elsevier.com/books/surfaces-and- their-measurement/whitehouse/978- 1- 4377-3465-6 Zhai, C., Hanaor, D., & Gan, Y. (2017). Contact stiffness of multiscale surfaces by truncation analysis. International Journal of Mechanical Sciences, 131. https://doi.org/10.1016/ j.ijmecsci.2017.07.018 Zhou, Q.-Y., Park, J., & Koltun, V. (2018). Open3D: A Modern Library for 3D Data Processing. arXiv:1801.09847.
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv	Atribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rights.uri.spa.fl_str_mv	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv	info:eu-repo/semantics/openAccess
rights_invalid_str_mv	Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
dc.format.extent.spa.fl_str_mv	xv, 73 páginas
dc.format.mimetype.spa.fl_str_mv	application/pdf
dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ciencias - Maestría en Ciencias - Física
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
bitstream.url.fl_str_mv	https://repositorio.unal.edu.co/bitstream/unal/86160/1/license.txt https://repositorio.unal.edu.co/bitstream/unal/86160/2/79925312.2024.pdf
bitstream.checksum.fl_str_mv	eb34b1cf90b7e1103fc9dfd26be24b4a 60c71b398bddd055b39d7e3767ad60a9
bitstream.checksumAlgorithm.fl_str_mv	MD5 MD5
repository.name.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv	repositorio_nal@unal.edu.co
_version_	1806886140423176192
spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Sandino del Busto, John William1316ac4e998635a011fdb61947d32faf600Gómez Mateus, José Alfredo28a402ef4c014072fc6fd3edbcdb128eMicroscopía Electrónica2024-05-24T20:58:20Z2024-05-24T20:58:20Z2023https://repositorio.unal.edu.co/handle/unal/86160Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasEsta investigación se enfoca en determinar la rugosidad superficial y su correlación con la dimensión fractal a partir de imágenes obtenidas mediante microscopía electrónica de barrido (SEM). Se empleó software libre para procesar imágenes y calcular parámetros de rugosidad y dimensión fractal en 3D. El estudio se centró en micrografías de una incisión en una lámina de aluminio, utilizando SIFT para detectar puntos característicos y el método de box counting para la dimensión fractal. Los resultados demostraron coherencia entre los perfiles de rugosidad medidos y los obtenidos mediante un perfilómetro, además de establecer correlaciones significativas entre la rugosidad promediada y la dimensión fractal. Este enfoque multidimensional proporciona una perspectiva más completa de la rugosidad, superando las limitaciones de las mediciones lineales y contribuyendo al entendimiento detallado de las superficies a nivel microscópico. (Texto tomado de la fuente).This research focuses on determining surface roughness and its correlation with the fractal dimension from images obtained through Scanning Electron Microscopy (SEM). Open-source software was used to process images and calculate roughness parameters and fractal dimension in 3D. The study centered on micrographs of an incision in an aluminum sheet, using SIFT to detect characteristic points and the box counting method for fractal dimension. The results demonstrated coherence between the measured roughness profiles and those obtained by a profilometer, in addition to establishing significant correlations between averaged roughness and fractal dimension. This multidimensional approach provides a more comprehensive perspective on roughness, overcoming the limitations of linear measurements and contributing to a detailed understanding of surfaces at the microscopic level.MaestríaMagíster en Ciencias - FísicaMicroscopía electrónicaxv, 73 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - FísicaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computación620 - Ingeniería y operaciones afines::621 - Física aplicadaRugosidadMicroscopio Electrónico de BarridoReconstrucción en 3DNubes de puntosAlgoritmos de detección de puntos característicosDimensión fractalRoughnessScanning Electron Microscopy3D reconstructionPoint cloudsFractal dimensionCharacteristic point detection algorithmsRugosidad (electrónica)microscopio electrónicodimensión fractalalgoritmoelectron microscopefractal dimensionalgorithmObtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de BarridoDetermination of roughness from images obtained with a Scanning Electron MicroscopeTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAkhtar, K., Khan, S. A., Khan, S. B. K., & Asiri, A. M. (2018). Scanning Electron Microscopy: Principle and Applications in Nanomaterials Characterization. Springer. https://doi.org/10.1007/978-3-319-92955-2 4Alcantarilla, P. F., Bartoli, A., & Davison, A. J. (2012). KAZE Features. Eur. Conf. on Computer Vision (ECCV)Arasan, S., Akbulut, S., & Hasiloglu, A. S. (2011). The relationship between the fractal dimension and shape properties of particles. KSCE Journal of Civil Engineering, 15 (7), 1219-1225. https://doi.org/10.1007/s12205-011-1310-xBarash, D., Israeli, M., & Kimmel, R. (2001). An Accurate Operator Splitting Scheme for Nonlinear Diffusion Filtering. En M. Kerckhove (Ed.), Scale-Space and Morphology in Computer Vision (pp. 281-289, Vol. 2106). Springer. https://doi.org/10.1007/3- 540-47778-0 25Bernardini, F., Mittleman, J., Rushmeier, H., Silva, C., & Taubin, G. (1999). The ballpivoting algorithm for surface reconstruction. IEEE Transactions on Visualization and Computer Graphics, 5 (4), 349-359Blachowski, A., & Ruebenbauer, K. (2009). Roughness method to estimate fractal dimension. Acta Physica Polonica A, 115 (3), 636-640Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 327 (8476), 307-310. https://doi.org/ 10.1016/S0140-6736(86)90837-8Bonetto, R. D., Ladaga, J. L., & Ponz, E. (2006). Measuring Surface Topography by Scanning Electron Microscopy. II. Analysis of Three Estimators of Surface Roughness in Second Dimension and Third Dimension. Microscopy and Microanalysis, 12, 178-186Botsch, M., Kobbelt, L., Pauly, M., Alliez, P., & L´evy, B. (2010). Polygon Mesh Processing. A K Peters/CRC PressBradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer vision with the OpenCV library. O’Reilly Media, IncBrown, M., & Lowe, D. G. (2002). Invariant features from interest point groups. British Machine Vision ConferenceCalonder, M., Lepetit, V., Strecha, C., & Fua, P. (2010). BRIEF: Binary Robust Independent Elementary Features. European conference on computer vision, 778-792Chongpu, Z., Hanaor, D., Proust, G., & Gan, Y. (2017). Stress-Dependent Electrical Contact Resistance at Fractal Rough Surfaces. Journal of Engineering Mechanics, 143 (3), B4015001. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000967Datatab. (2021). Tutorial: Kendall’s Tau. Consultado el 8 de diciembre de 2023, desde https: //datatab.es/tutorial/kendalls-tauDektak 150 Profiler User’s Manual [Available from Veeco Instruments Inc., (www.veeco.com)]. (2007). Veeco Instruments Inc. Plainview, NY.Edelsbrunner, H., Kirkpatrick, D. G., & Seidel, R. (1983). On the shape of a set of points in the plane. IEEE Transactions on Information Theory, 29 (4), 551-559.Elcometer. (2022). Rugosímetro MarSurf PS1 Elcometer 7061 [ Último acceso: 2023-04-04]. http ://www.elcometer .com/es/inspeccin - revestimientos/limpieza- de- superficie - perfil - de - la - superficie / rugosidad - de - la - superficie / rugosimetro - marsurf - ps1 - elcometer-7061.htmlEl-Gomati, M. M., Wells, T., Zha, X., Sykes, R., Russo, C. J., Henderson, R., & McMullan, G. (2021). 100 keV vacuum sealed field emission gun for high resolution electron microscopy. Journal of Vacuum Science & Technology B, 39 (6), 062804. https://doi. org/10.1116/6.0001275Forum, O. Q. (2013, agosto). Is SURF algorithm used in OPENCV patented? https : / / answers.opencv.org/question/18259/is-surf-algorithm-used-in-opencv-patented/Forum, O. Q. (2020, noviembre). Expired US patent on SIFT. https://answers.opencv.org/ question/238447/expired-us-patent-on-sift/Gadelmawla, E., Koura, M., Maksoud, T., Elewa, I., & Soliman, H. (2002). Roughness parameters. Journal of Materials Processing Technology, 123 (1), 133-145. https://doi. org/https://doi.org/10.1016/S0924-0136(02)00060-2Goldstein, J. I., Newbury, D. E., Joy, D. C., Lyman, C. E., Echlin, P., Lifshin, E., Sawyer, L., & Michael, J. R. (2003). Scanning Electron Microscopy and X-Ray Microanalysis. Springer.Gontard, L., L´opez-Castro, J., Gonz´alez-Rovira, L., V´azquez-Mart´ınez, J., Varela-Feria, F., Marcos, M., & Calvino, J. (2017). Assessment of engineered surfaces roughness by high-resolution 3D SEM photogrammetry. Ultramicroscopy, 177, 106-114. https:// doi.org/https://doi.org/10.1016/j.ultramic.2017.03.007Hanaor, D., Gan, Y., & Einav, I. (2016). Static friction at fractal interfaces. Tribology International, 93, 229-238. https://doi.org/10.1016/j.triboint.2015.09.016Hartley, R., & Zisserman, A. (2003). Multiple View Geometry in Computer Vision. Cambridge University PressHenao-Londoño, J. C., Riaño-Rojas, J. C., Gómez-Mendoza, J. B., & Restrepo-Parra, E. (2018). 3D Stereo Reconstruction of SEM Images. Modern Applied Science, 12 (12), 57. https://doi.org/10.5539/mas.v12n12p57Kalvani, P. R., Jahangiri, A. R., Shapouri, S., Sari, A., & Jalili, Y. S. (2019). Multimode AFM analysis of aluminum-doped zinc oxide thin films sputtered under various substrate temperatures for optoelectronic applications. Superlattices and Microstructures, 132, 106173. https://doi.org/10.1016/j.spmi.2019.106173Kayaalp, A., Rao, A. R., & Jain, R. (1990). Scanning Electron Microscope-Based Stereo Analysis. Machine Vision and Applications, 3, 231-246.Kazhdan, M., Bolitho, M., & Hoppe, H. (2006). Poisson surface reconstruction. Proceedings of the fourth Eurographics symposium on Geometry processing, 7.Koga, D., Kusumi, S., Shibata, H., & Watanabe, M. (2021). Applications of Scanning Electron Microscopy Using Secondary and Backscattered Electron Signals in Neural Structure. Frontiers in Neuroanatomy, 15. https://doi.org/10.3389/fnana.2021.647428Li, Y., Shum, H.-Y., Tang, C.-K., & Szeliski, R. (2004). Stereo reconstruction from multiperspective panoramas. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26 (1), 45-62. https://doi.org/10.1109/TPAMI.2004.1261078Lin Chen, F. R., & Heipke, C. (2021). Feature detection and description for image matching: from hand-crafted design to deep learning. Geo-spatial Information Science, 24 (1), 58-74. https://doi.org/10.1080/10095020.2020.1843376Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30 (2), 77-116Liu, Z., Wang, Y., Chen, J., Li, X., & Zhang, Z. (2019). Anisotropy of surface roughness of metals. Applied Surface Science, 479, 796-805. https://doi.org/10.1016/j.apsusc. 2019.02.163Lowe, D. G. (1999). Object recognition from local scale-invariant features. Proceedings of the seventh IEEE international conference on computer vision, 2, 1150-1157.Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60 (2), 91-110.Luo, W., Schwing, A. G., & Urtasun, R. (2016). Efficient Deep Learning for Stereo Matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 5695-5703.Ma, Z., & Liu, S. (2018). A review of 3D reconstruction techniques in civil engineering and their applications. Advanced Engineering Informatics, 37, 163-174. https://doi.org/ https://doi.org/10.1016/j.aei.2018.05.005Majumdar, A., & Bhushan, B. (1990). Fractal Characterization and Simulation of Rough Surfaces. American Society of Mechanical EngineersMandelbrot, B. (1983). The Fractal Geometry of Nature. Henry Holt; Company. https:// books.google.com.co/books?id=0R2LkE3N7-oCMate, C. M. (2008). Tribology on the Small Scale: Mesoscopic Physics and Nanotechnology. Oxford University PressMilanese, E., Brink, T., Aghababaei, R., & Molinari, J.-F. (2019). Emergence of self-affine surfaces during adhesive wear. Nature Communications, 10 (1), 1116. https://doi. org/10.1038/s41467-019-09127-8Minitab. (2021). Estadísticos y gráficas para t de 1 muestra. Consultado el 8 de diciembre de 2023, desde https://support.minitab.com/es-mx/minitab/21/help-and-howto/ statistics/basic-statistics/how-to/1-sample-t/interpret-the-results/all-statisticsand- graphs/Moeslund, T. B. (2012). BLOB Analysis. En Introduction to Video and Image Processing: Building Real Systems and Applications (pp. 103-115). Springer London. https://doi. org/10.1007/978-1-4471-2503-7 7Montakhabi, F., Poursaeidi, E., Rahimi, J., & Sigaroodi, M. R. J. (2022). Investigation of the effect of BC layer surface roughness and TC layer porosity on stress values in plasma sprayed coatings based on SEM images. Materials Today Communications, 33, 104737. https://doi.org/https://doi.org/10.1016/j.mtcomm.2022.104737Moons, T., Van Gool, L., & Vergauwen, M. (2009). 3D Reconstruction from Multiple Images: Part 1 - Principles. Foundations and Trends in Computer Graphics and Vision, 4, 287-404Nayak, S. R., Mishra, J., & Palai, G. (2019). Analysing roughness of surface through fractal dimension: A review. Image and Vision Computing, 89, 21-34. https://doi.org/https: //doi.org/10.1016/j.imavis.2019.06.015Odling, N. E. (1994). Natural fracture profiles, fractal dimension and joint roughness coefficients. Rock Mechanics and Rock Engineering, 27 (3), 135-153. https://doi.org/10. 1007/BF01020307Oho, E. (2002). Digital image-processing technology useful for scanning electron microscopy and its practical applications. En P. W. Hawkes (Ed.), Electron Microscopy and Holography II (pp. 251-IV, Vol. 122). Elsevier. https://doi.org/https://doi.org/10. 1016/S1076-5670(02)80054-4Oliveira, S. M. (2005). Analysis of Surface Roughness and Models of Mechanical Contacts [Tesis de grado]. Universita di PisaOpen3D. (2023). Surface Reconstruction. http://www.open3d.org/docs/release/tutorial/ geometry/surface reconstruction.htmlOpenCV. (2021). Understanding Features [Consultado el 15 de Octubre de 2022]. https : //docs.opencv.org/3.4/df/d54/tutorial py features meaning.htmlParker, K. A., Ribet, S., Kimmel, B. R., dos Reis, R., Mrksich, M., & Dravid, V. P. (2022). Scanning Transmission Electron Microscopy in a Scanning Electron Microscope for the High-Throughput Imaging of Biological Assemblies. Biomacromolecules, 23 (8), 3235-3242. https://doi.org/https://doi.org/10.1021/acs.biomac.2c00323Parsons, D. F., Walsh, R. B., & Craig, V. S. J. (2014). Surface forces: Surface roughness in theory and experiment. Journal of Chemical Physics, 140 (16), 164701. https://doi. org/10.1063/1.4871412Perona, P., & Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (7), 629-639.Pfeifer, P. (1988). Fractals in Surface Science: Scattering and Thermodynamics of Adsorbed Films. En R. Vanselow & R. Howe (Eds.), Chemistry and Physics of Solid Surfaces VII (pp. 283-305, Vol. 10). Springer Berlin Heidelberg. https://doi.org/10.1007/978- 3-642-73902-6 10Quan, L. (2010). Image-based modeling. Springer Science & Business Media.QuestionPro. (2020). Coeficiente de correlación de Spearman: ¿Qué es y cómo se calcula? Consultado el 8 de diciembre de 2023, desde https://www.questionpro.com/blog/es/ coeficiente-de-correlacion-de-spearman/Reimer, L. (1998). Scanning Electron Microscopy: Physics of Image Formation and Microanalysis. Springer.Rivera, M. H., & Melo, M. E. R. (2001). La rugosidad de las superficies: Topometría. Ingenierías, 4, 27-33.Rosin, P. L. (1999). Measuring corner properties. Computer Vision and Image Understanding, 73 (2), 291-307.Rosten, E., & Drummond, T. (2006). Machine learning for high-speed corner detection. European conference on computer vision, 430-443.Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011). ORB: an efficient alternative to SIFT or SURF. in Proc. of the IEEE International Conf. on Computer Vision (ICCV).Sarode, V. (2022). What Are Point Clouds? https://medium.com/analytics-vidhya/whatare- point-clouds-3655d565e142Sato, H., O-Hori, M., & Nakayama, K. (1982). Surface Roughness Measurement by Scanning Electron Microscope. CIRP Annals, 31 (1), 457-462. https://doi.org/https://doi.org/ 10.1016/S0007-8506(07)63347-2Shet, V., & Picard, R. W. (2005). Python for scientific computing. Computing in Science & Engineering, 7 (3), 10-20Sun, T., Li, Y., Liu, Y., Deng, B., Liao, C., & Zhu, Y. (2023). Advanced scanning electron microscopy and microanalysis: Applications to nanomaterials. En Y. Yin, Y. Lu & Y. Xia (Eds.), Encyclopedia of Nanomaterials (First Edition) (First Edition, pp. 183-209). Elsevier. https://doi.org/https://doi.org/10.1016/B978-0-12-822425-0.00104-4Team, O. (2023). Feature Detection and Description. https://docs.opencv.org/4.x/d5/d51/ group features2d main.htmlTESCAN a.s. (2014). Scanning Electron Microscope: Instructions for Use. TESCAN. https: //www.csuchico.edu/sem/ assets/documents/vega-manual-2014.pdfThäle, C., & Freiberg, U. (2008). A Markov Chain Algorithm for Determining Crossing Times Through Nested Graphs. Discrete Mathematics & Theoretical Computer Science.Töberg, S., & Reithmeier, E. (2020). Quantitative 3D Reconstruction from Scanning Electron Microscope Images Based on Affine Camera Models. Sensors, 20 (12), 3598. https: //doi.org/10.3390/s20123598Vanderbilt University. (s.f.). The Hausdorff DimensionViper, Q. (2022). Making Fractal Shapes with PythonWang, J., Wu, Y., Cao, Y., et al. (2020). Influence of surface roughness on contact angle hysteresis and spreading work. Colloid and Polymer Science, 298, 1107-1112. https: //doi.org/10.1007/s00396-020-04680-xWang, Y., Liu, R., Ji, H., Li, S., Yu, L., & Feng, X. (2022). Correlating mechanical properties to fractal dimensions of shales under uniaxial compression tests. Environmental Earth Sciences, 82 (1), 2. https://doi.org/10.1007/s12665-022-10642-zWeickert, J., Ishikawa, S., & Imiya, A. (1999). Linear scale-space has first been proposed in Japan. Journal of Mathematical Imaging and Vision, 10.Weisstein, E. W. (2023). Menger SpongeWhitehouse, D. J. (2010). Surfaces and their Measurement. Butterworth-Heinemann. https: //www.elsevier.com/books/surfaces-and- their-measurement/whitehouse/978- 1- 4377-3465-6Zhai, C., Hanaor, D., & Gan, Y. (2017). Contact stiffness of multiscale surfaces by truncation analysis. International Journal of Mechanical Sciences, 131. https://doi.org/10.1016/ j.ijmecsci.2017.07.018Zhou, Q.-Y., Park, J., & Koltun, V. (2018). Open3D: A Modern Library for 3D Data Processing. arXiv:1801.09847.EstudiantesInvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/86160/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL79925312.2024.pdf79925312.2024.pdfTesis de Maestría en Ciencias - Físicaapplication/pdf35592354https://repositorio.unal.edu.co/bitstream/unal/86160/2/79925312.2024.pdf60c71b398bddd055b39d7e3767ad60a9MD52unal/86160oai:repositorio.unal.edu.co:unal/861602024-05-24 16:00:44.811Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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

Obtención de la rugosidad a partir de imágenes obtenidas en un Microscopio Electrónico de Barrido

Publicaciones similares