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
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/86160
- Palabra clave:
- 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
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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|
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. |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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xv, 73 páginas |
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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 |
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Universidad Nacional de Colombia - Sede Bogotá |
institution |
Universidad Nacional de Colombia |
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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. 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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.pdf60c71b398bddd055b39d7e3767ad60a9MD52THUMBNAIL79925312.2024.pdf.jpg79925312.2024.pdf.jpgGenerated Thumbnailimage/jpeg4792https://repositorio.unal.edu.co/bitstream/unal/86160/3/79925312.2024.pdf.jpg830e2d9638d249c759d73db725fcec8cMD53unal/86160oai:repositorio.unal.edu.co:unal/861602024-08-25 23:10:51.414Repositorio Institucional Universidad Nacional de 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