Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

Mora de Sambricio, Javier and Gallego Galán, Ángel and Otero Marnotes, Andres and Torre Arnanz, Eduardo de la and Riesgo Alcaide, Teresa (2013). Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform. In: "Conference on Design and Architectures for Signal and Image Processing (DASIP)", 08/10/2013 - 10/10/2013, Cagliari, Italy. pp..

Description

Title: Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform
Author/s:
  • Mora de Sambricio, Javier
  • Gallego Galán, Ángel
  • Otero Marnotes, Andres
  • Torre Arnanz, Eduardo de la
  • Riesgo Alcaide, Teresa
Item Type: Presentation at Congress or Conference (Article)
Event Title: Conference on Design and Architectures for Signal and Image Processing (DASIP)
Event Dates: 08/10/2013 - 10/10/2013
Event Location: Cagliari, Italy
Title of Book: Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform
Date: 2013
Subjects:
Freetext Keywords: Evolvable hardware; evolutionaryalgorithms; adaptivesystems; imagefilter; referenceimage; camera
Faculty: Centro de Electrónica Industrial (CEI) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

More information

Item ID: 29511
DC Identifier: http://oa.upm.es/29511/
OAI Identifier: oai:oa.upm.es:29511
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6661538&queryText%3DNoise-agnostic+adaptive+image+filtering+without+training+references+on+an+evolvable+hardware+platform
Deposited by: Memoria Investigacion
Deposited on: 27 Apr 2015 18:45
Last Modified: 27 Apr 2015 18:45
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