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Sensors 2017, 17(5), 981; doi:10.3390/s17050981

A Genetic Algorithm for the Generation of Packetization Masks for Robust Image Communication

1
Magister en Ciencias de la Computación, Universidad del Bío-Bío, Chillán 3800708, Chile
2
Departamento de Ingeniería Eléctrica y Electrónica, Universidad del Bío-Bío, Concepción 4051381, Chile
3
Departamento de Ciencias de la Computación y Tecnologías de la Información, Universidad del Bío-Bío, Chillán 3800708, Chile
4
Centre de Recherche en Automatique de Nancy, Université de Lorraine, CNRS, Vandœuvre-lès-Nancy 54506, France
5
Magister en Informática, Universidad del Bío-Bío, Concepción 4051381, Chile
6
Corporación Educacional Colegio Concepción, Nuble 3800564, Chile
*
Author to whom correspondence should be addressed.
Academic Editor: Jaime Lloret Mauri
Received: 31 January 2017 / Revised: 24 March 2017 / Accepted: 7 April 2017 / Published: 28 April 2017
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [705 KB, uploaded 28 April 2017]   |  

Abstract

Image interleaving has proven to be an effective solution to provide the robustness of image communication systems when resource limitations make reliable protocols unsuitable (e.g., in wireless camera sensor networks); however, the search for optimal interleaving patterns is scarcely tackled in the literature. In 2008, Rombaut et al. presented an interesting approach introducing a packetization mask generator based in Simulated Annealing (SA), including a cost function, which allows assessing the suitability of a packetization pattern, avoiding extensive simulations. In this work, we present a complementary study about the non-trivial problem of generating optimal packetization patterns. We propose a genetic algorithm, as an alternative to the cited work, adopting the mentioned cost function, then comparing it to the SA approach and a torus automorphism interleaver. In addition, we engage the validation of the cost function and provide results attempting to conclude about its implication in the quality of reconstructed images. Several scenarios based on visual sensor networks applications were tested in a computer application. Results in terms of the selected cost function and image quality metric PSNR show that our algorithm presents similar results to the other approaches. Finally, we discuss the obtained results and comment about open research challenges. View Full-Text
Keywords: robust image communication; packetization method; block interleaving; genetic algorithms; camera sensor networks robust image communication; packetization method; block interleaving; genetic algorithms; camera sensor networks
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MDPI and ACS Style

Zapata-Quiñones, K.; Duran-Faundez, C.; Gutiérrez, G.; Lecuire, V.; Arredondo-Flores, C.; Jara-Lipán, H. A Genetic Algorithm for the Generation of Packetization Masks for Robust Image Communication. Sensors 2017, 17, 981.

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