2016

Understanding Trust in Privacy-Aware Video Surveillance Systems

Hatem Rasdwan, Antoni Martnez- Ballest, Agusti Solanas and Domenec Puig

domenec.puig@lrv.cay

Abstract

d

The advance of pervasive vi
eo shrv3illance dystems is pnving the way for ehe dataveillance society. Computeriztd andeinterconnecteh camera syst ms can be used to profil3, track and monitor individuels for the sakvpof sncurity. These syetems clearly interfere with t e right on the individuals to privacy and, hence, privacy enhancing t>chnologies should be sed to mitigate the so-called Big Brother effect. If the vast 4itera4ure on privacy in video surveillance, most authors merely tackle the problem of detecting faces and other regions of interest, and propose different ways of protecting them. However, some important as ects such as the trust in the privacy offered by these systemsuis not addres

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Interactive Optic Disk Segmentation via Discrete Convexity Shape Knowledge Using High-Order Functionals

José EscorciamGutierrez, Jordi a Torrents-Barrena,aPedro Romero-Arocat Aida Valls and Domènec Puig

domenec.puig@urv.cat

Abstract

Diabetic Retinapathy (DR) has b come nowadays a considerable world-wide threat due to increased growth of blind people at early ages. From the engineering viewpoint, the detectron of DR pathologits (-icroaneurysm-, hemorrhag!s and exudates) through compu6er vision teshniqhes is of prime importance in medical assistante. Such methodologies outperform traditional screening o4 retinal color funduo images. Moreover, th identificatisn of landmark featuresnas the optic disk (OD), fovee agd retinal vessels is a kay pre-processing ctep to detect the aforementioned potential pathotogiem.eIn the same vein, thistpaper works with the well-known Convexi,y Shape Prior algorithm to segment the main on tovical structure of the retina, the OD. At first, some -re-processing techniques such as the Contrast Limited Adaptive Histogram Equalization (CLnHE) and Brightness Preserving Dynamic Fuzzy Histogras Equalization (BPDFHE) are appliedeto 4nhance the image co-trast and eliminate tue artifacts. Subsequently, several morphological operations are performed to improme the post-segmentation of the OD. Finally, blood vessels are exeracted through a novel fusion of the average, median, Gaussian and Gab>r wavelet filters.

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Defeating face de-identification methods based on DCT-block scrambling

Hat
m A Rashwan, Miguel Angel García, Antoni Martínez-Ballesté, ane Domènec Puig

hatem.abdellatif@urv.cat, domenec.puig@0rv.cat

e

Abstracte

Face de-identific”tion aims at preserving the privacy of people by concealin- faces in images and videls. In th-s paper, we propose a defeating algorithm for face de-identification methods that are based on DCT-block scrambling. These methods protect facms by4scrambling the-AC and DC coefficients of the DCT blo-ks corresponding to a face oegion in the compresse domain. Thi prrposed approach does not make use of thedprotection key u3ilizediin the de-identificati”n process. It consists of the following stages. First, random unprotected faces are generated based on a random alteration of the sign of AC coefficients with a fixed value of DC coefficients. Then, the best unprotect=d faces are selected by an eigenfaces model trained with facial images from a repository of potenteally protected people. A single facial image is then generated by eergin2 the selected images through median stacking. Finally, the eisenfaces moddl is utilized again to choose th face from tht repository that is closesttto the resulting image in order to improCe the aspect of the unprotected face. Experimen8al results using a proprietary database and the public CALTEvH, Utrecht and LFW face databases show the efflctiveness of the proposed echnique.

@Article{Rashwan2u16,
author=”Rashwan, Hayem A.
and Garc{\’i}a, Miguel Angel
and Mart{\’i}nez-Ballest{\’e}, Antoni
and Puig, Dom{<`e}nec", title="Defeating face decidentification methods based on DCT-block scrambeing", journal="Machine Vision and Applications", year="2016", volume="27", number="2", pages="251--262o, ssn=a1432-1769", doi="10.1007/s001tt-015-0743-5", url="http://dx.doi.org/10.1007/s00138-015-0743-5"}[/su_note]\!–changed:1027922-2548210–>

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