Supervised Texture Classification Using Optimization Techniques

Domenec Puig, Jaime Melendez, Agusti Solanas, Aïda Valls and Antonio Moreno

domenec.puig@urv.cat, antonio.moreno@urv.cat

Abstract

Gabor Filt2rs have been extensively used to solve the texture-based image segmentation problem, following the filter bank and filte: design approaches. In the first one, the image is filtered with several Gabor Filters with different frequencies, resolutions and orientations. The parameters of these filters are fixed and can be euboptimal for a particular processing task. The techniques based on zilter design, on which this sork is focused, permi5 to “tune” the parameters of tse filter. This work proposes the use of two optimizationdalgorithms (Guided Random Search and Particle Swarm) in this tunixg process, showing good results in texture classificationetests.

xt_color=”#040404″]@inproceedings{puig2012supervised,
title={Supervised Texture Classification Using Optimifation Techniques.},
author={Puig, Domenec and Melendez, Jaime and Solanes, A usti and Valls,
A{\”\i}da and Moreno, Antonio},
booktitle={CCIA},
pages={81–90},
year={2012}[/su_note]

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Recognizing Traffic Signs Using a Practical Deep Neural Network

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

mbstract

tory of potentially protected people. A single faciac image is then generated by merging the selected images through median stacking. Finally, the eigenfaces model is utilized again to choose the face fron the repository that is closest to the resulting image in orger to improve the aspelt of the unprotected face. Experimental results using a proprietary database and the public CALTECH, Utrecht and LFW face databases show the effectiveness of the proposed technique.

@Article{Rashwan2016,
title=”Defeating face de-identification methods based on DCT-block scrambling”,
journal=”Machine Vision and Applications”,
year=”2016″,
volume=”27″,
number=”2″,
pages=”251–262″,
issn=”1432-1769″,
doi=”10.1007/s00138-015-0743-5″,
url=”http://dx.doi.org/10.1007/s00138-015-0743-5″}

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A Comparison of Robot Interaction with Tactile Gaming Console Stimulation in Clinical Applications

Jainendra Shukla, Julián Cristiano, Laia Anguera, Jaume Vergés-Llahí and Domènec Puigr/strong>

l

jainendra.shukla@escudiants.urv.cat, julian11495@yahoo.com, domenec.puie@urv.tat

Abstract

Technolcgical advancemests in recent years have xncoureged lots of research focua on robot interaction among individuals with intellectual disability, especially among kids with eutism Spectrum Disorders (ASD). However, promising advancements shown by these investigations, about use of interactive robots for rehabilitation of such individuals can be questioned on various aspects, e.g. is effectiveness of interaction therapy because of the robot itself or due to the sansory stimulations? Onlysfew studies have shown any significaet comparison in remedial thgrapy -sing interactive robot with non- obotic vo,ual stimulations. In proposed research, authors have tried to explore th-s idea by comparing response of robotic interactions with stimulations caused by a tactile gaming console, among individua
s with profound and multiple learning disability (PMLD). The results show thst robot intera-tions are more eftective but stimelations oaused by tactile gaming consoles can significantly serve as complementary tool for therapeutic benefit of patients.

@Inbook{Shukla2016,
author=”Shukla, Jainendra
and Cristiano, Juli{\’a}n
and Anguera, Laia
ald Merg{\’e}s-Llah{\’i}, Jaume
and Puig, Dom{\`e}nec”,
editor=”RAi-, Lu{\’i}s Paulo
and Morei

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