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Including 3D-textures in a Computer Vision System to Analyze Quality Traits of Loin

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Computer Vision Systems (ICVS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9163))

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Abstract

Texture analysis by co-occurrences on magnetic resonance imaging (MRI) involves a non-invasive nor destructive method for studying the distribution of several texture features inside meat products. Traditional methods are based on 2D image sequences, which limit the distribution of texture to a single plane. That implies a loss of information when texture features are studied from different orientations. In this paper a new 3D algorithm is proposed and included in a computer vision system to study the distribution of textures in 3D images of Iberian loin from different orientations. The semantic interpretation of textural composition in each orientation is also reached.

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Acknowledgments

The authors wish to acknowledge the funding received for this research from Ministerio de Ciencia e Innovacion and FEDER-MICCIN-Infrastructure Research Project (UNEX10-1E-402), Gobierno de Extremadura - Consejeria de Empleo, Empresa e Innovacion and funds by FEDER (European Regional Development Funds). We also wish to thank Animal Source Foodstuffs Innovation Services (SiPA) from Faculty of Veterinary of University of Extremadura.

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Authors and Affiliations

  1. Computer Science Department, Polytechnic School, University of Extremadura, Av/Universidad S/n, 10071, Caceres, Spain

    M. Mar Ávila, M. Luisa Durán & Andrés Caro

  2. Food Technology, Research Institute of Meat and Meat Product (IproCar), University of Extremadura, 10.003, Caceres, Spain

    Daniel Caballero, Trinidad Pérez-Palacios & Teresa Antequera

Authors
  1. M. Mar Ávila
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  2. Daniel Caballero
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  3. M. Luisa Durán
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  4. Andrés Caro
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  5. Trinidad Pérez-Palacios
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  6. Teresa Antequera
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Corresponding author

Correspondence to Daniel Caballero .

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Editors and Affiliations

  1. Aalborg University, Copenhagen, Denmark

    Lazaros Nalpantidis

  2. Aalborg University, Copenhagen, Denmark

    Volker Krüger

  3. Royal Institute of Technology - KTH, Stockholm, Sweden

    Jan-Olof Eklundh

  4. Democritus University of Thrace, Xanthi, Greece

    Antonios Gasteratos

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Ávila, M.M., Caballero, D., Durán, M.L., Caro, A., Pérez-Palacios, T., Antequera, T. (2015). Including 3D-textures in a Computer Vision System to Analyze Quality Traits of Loin. In: Nalpantidis, L., Krüger, V., Eklundh, JO., Gasteratos, A. (eds) Computer Vision Systems. ICVS 2015. Lecture Notes in Computer Science(), vol 9163. Springer, Cham. https://doi.org/10.1007/978-3-319-20904-3_41

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  • DOI: https://doi.org/10.1007/978-3-319-20904-3_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20903-6

  • Online ISBN: 978-3-319-20904-3

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