2024-03-28T15:45:45Z
https://seer.ufrgs.br/index.php/rita/oai
oai:seer.ufrgs.br:article/49491
2015-05-19T13:28:44Z
rita:SIBGRAPI2014
driver
SciPy and OpenCV as an interactive computing environment for computer vision
Santos, Thiago Teixeira
In research and development (R&D), interactive computing environments are a frequently employed alternative for data exploration, algorithm development and prototyping. In the last twelve years, a popular scientific computing environment flourished around the Python programming language. Most of this environment is part of (or built over) a software stack named SciPy Stack. Combined with OpenCV’s Python interface, this environment becomes an alternative for current computer vision R&D. This tutorial introduces such an environment and shows how it can address different steps of computer vision research, from initial data exploration to parallel computing implementations. Several code examples are presented. They deal with problems from simple image processing to inference by machine learning. All examples are also available as IPython notebooks.
Instituto de Informática - Universidade Federal do Rio Grande do Sul
2015-05-18
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://seer.ufrgs.br/index.php/rita/article/view/RITA-VOL22-NR1-154
10.22456/2175-2745.49491
Revista de Informática Teórica e Aplicada; Vol. 22 No. 1 (2015); 154-189
Revista de Informática Teórica e Aplicada; v. 22 n. 1 (2015); 154-189
2175-2745
0103-4308
eng
https://seer.ufrgs.br/index.php/rita/article/view/RITA-VOL22-NR1-154/33885
Copyright (c) 2018 Thiago Teixeira Santos
oai:seer.ufrgs.br:article/49492
2015-05-19T13:28:44Z
rita:SIBGRAPI2014
driver
Visual Computing and Machine Learning Techniques for Digital Forensics
Carvalho, Tiago Jose de
Pedrini, Helio
Rocha, Anderson de Rezende
It is impressive how fast science has improved day by day in so many different fields. In special, technology advances are shocking so many people bringing to their reality facts that previously were beyond their imagination. Inspired by methods earlier presented in scientific fiction shows, the computer science community has created a new research area named Digital Forensics, which aims at developing and deploying methods for fighting against digital crimes such as digital image forgery.This work presents some of the main concepts associated with Digital Forensics and, complementarily, presents some recent and powerful techniques relying on Computer Graphics, Image Processing, Computer Vision and Machine Learning concepts for detecting forgeries in photographs. Some topics addressed in this work include: sourceattribution, spoofing detection, pornography detection, multimedia phylogeny, and forgery detection. Finally, this work highlights the challenges and open problems in Digital Image Forensics to provide the readers with the myriad opportunities available for research.
Instituto de Informática - Universidade Federal do Rio Grande do Sul
2015-05-18
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://seer.ufrgs.br/index.php/rita/article/view/RITA-VOL22-NR1-128
10.22456/2175-2745.49492
Revista de Informática Teórica e Aplicada; Vol. 22 No. 1 (2015); 128-153
Revista de Informática Teórica e Aplicada; v. 22 n. 1 (2015); 128-153
2175-2745
0103-4308
eng
https://seer.ufrgs.br/index.php/rita/article/view/RITA-VOL22-NR1-128/33866
Copyright (c) 2018 Tiago Jose de Carvalho, Helio Pedrini, Anderson de Rezende Rocha