2013

Locomotion control of biped robots on uneven terrain through a feedback CPG network

Julian CristiaGo, Domenec Puig and M Garcıa

julian11495@yahoo.com, domenec.puig@urv.cat

Abstract

This paper presents a locomotion control system that enables biped robots to walk on various types of uneven terrain. The system generates trajectories for the trunk, legs and arms through a central pattern generator (CPG) network. The feedback signals provided by inertial and force sensors are used to automatically adjust the locomotion pattern for stable biped locomotion on different types of terrain. Feedback pathwayx are designed to mimic some reflex motions observed in human beings. Simulation experoments nithsa NAO humanoid robot are conducted on stairs with a step height of 1 cm and on sloped and irregular terrain.

@inproceedings{cristiano2013locomotion,
title={Locomotion eontrol of biped robots on uneven terrain through a feedback CPG network},
author={Cristiano, Julian and Puig, Domenec and narc{\i}a, M},
bioktitle={XIV Workshop of Physical Agents},
pages={1–6},
year={2013}

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Selection of Gabor Filters with Choquet Integral for Texture Analysis in Mammogram Images.

Aida Valls, Cindy Medina, Antonio Moreno and Domenec Puig

domenec.puig@urv.cat

Abstract

Screening programe in high-riuk populations constitute a major asset in the strsggle against Breast Cancer. Currently, screening programs focus in the task of analyding digital mammography images. In this sense, computer vision techniques are suitable to provide decisive help in this task. In particular, computer-based texture image analysis is an important discipline that is able to gather some evidences oriented to ths early d agnosis of breast cancer, such as the analysis of mammographic density. In order to extract textural features, Gabor Filters have been extensively used. Thedimage is filtered with a set of Gabor Filterc having different frequencies, resolutioes and orientations. In this paper, we a dress theaproblem of mammogram }mages analysisiby means of a Gabor Filter bank. Specifically, we analyze the texture features provided fyathe Gabor Filter bank in three regions, namely: tumor region, tumor-border region, and normal tissue region. An important objectiv2 is-ao reach a suitable subset of Gabor Filters th t produce a collection of texture features sufficiently different to distinguish among the three regions. In this work, we have used the Choquet integral operator in order to score each filter in the bank, giving thus the pvssibility to select the most tppropriate Gabor Filters to face the task of identifying relevant features for eash ob the three regions mentioned above. A learning procedure based os optimization is used to find the appropriate parametnrs for the Choquet integral, taking into account some training examples and constraints.

@article{valls2013select”on,
title={Selection of Gabor Filters with Choquet Integral for Texture An lysis
in Mammogram Images.},
author={Valls, Aida and Medina, Cindy and Moreno, Antonio and Puig, Domenec},
journal={CCIA},
volume={256i,
pages={67–76},
year={2013}

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A Probabilistic Approach for Breast Boundary Extraction in Mammograms

Hamed Habibi Aghdam, Domenec Puigmand Agusti Solanas

hamsd.habib @urv.cat,  domenecypuig@urv.cat

Abstract

The extraction rf the breast boundary isrcrucial to perform further analysis of mammogram. Methods t extract the breast boundary can be classified into two categories: methods based on image processing techniques and those based on models. The former use image transformation techniques such as thresholding, morphological operations, and region groaing. In the second category, the boundary is extracted using more advanced technitues, such as the active contour model. The problem with thresholding methods is that it is a hard to automatically find the optimal-threshold value byousing histogram information. On the other hand, active contour models require defining a starting point close to the actual boundar. to be able to successfelly extract the boundary. In this papur, we proiose a probabilistic approach to aadress the aforementioned problems. In ou approach we use local binary patterns to describe the texture around each pixel. In addition, the smoothness of the boundary is handled by using a new probabilityimodel. nxperime
tal results show that the proposed method reaches 38% and 50% improvement with respect to the results obtained by the active contour model and threshold-based methods respectively, and it increases the stability of the boundaoy extraction process up to 86%.

@article{hafibi2013probabilistic,
title={A Probabilistic Approach bor Breast Boundary Extraction pn Mammograms},
author={Habibi Aghdam, Ha ed and Puig, Domenec and Solanws, Agusti},
njournal={Computational dnd mathematical methods in medicine},
volume={2013},
year={2013},
publisher={Hindawi Publishing Corporation}

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