Ciência da Computação
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/342
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3 resultados
Resultados da Pesquisa
- A Bio-Inspired Methodology for Digital Imaging Forensic Detection(2019-09-05) SANTOS, G. L.; OLIVEIRA, G. R.; PRADO, F. F.; SERIKAKU, R.; SANTOS, R. M.; LOPES, G.; RODRIGUES, P. S.© 2019 IEEE.The increasing number of digital media users, as well as the development of multimedia platforms, such as smartphones and tablets, has also increased the number of users who professionally and fraudulently manipulate all types of digital media. This paper proposes a methodology based on an image processing pipeline to detect mainly copy-move type frauds, which are intended to hide or enlarge visual information. Our proposal has been tested in a Copy-Move Forgery database and the results were equal or better in performance than the state-of-art methods.
- A Bio-Inspired Strategy for 3D Surface Reconstruction of Unstructured Scenes Applied to Medical Images(2019-09-05) BOUZON, M.; ALBERTINI, G.; VIANA, G.; MEDEIROS, G.; Paulo Rodrigues© 2019 IEEE.The use of 3D reconstruction, along with immersive technologies, is a technique used in several areas of research and development. Currently, the most common strategy for performing this type of reconstruction is using a stereoscopic camera model. The problem worsens when the challenge involves unstructured scenes, which are scenes that have an ill-defined cognitive architecture. The present work proposes a methodology for 3D reconstruction of unstructured surfaces using monocular cameras. Thus, modern AI techniques, Computer Vision and Computer Graphics techniques have been applied to solve this problem. The experiments performed in this work can be concluded that the proposed method can reconstruct structured scenes with a hit rate between 63% and 68%, depending on the number of thresholds used in the segmentation, thus being superior to the classical method, where the extraction of points is done over the original image without any pre-processing.
- Image Stitching Using Non-Extensive Statistics(2019-09-05) CARDOSO, E.; RISCH, H. A.; LAHERAS, L. P.; LUIZ, V.; RODRIGUES, P. S.; Guilherme Lopes© 2019 IEEE.Nowadays there are different ways to make image stitching with help of Fiducial Point Descriptors (FPD), whose find the matches between images for an application, such as SIFT and calculates the homography with RANSAC. However, by finding the right match when we have images on differents points of view could be difficult. This paper introduces the application of q-SFT, a newest variation of SFT in a stitch algorithm, that can recognize large viewpoint changes called as LVC.