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Towards Assistive Solutions for People with Central Vision Loss

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Book cover Natural and Artificial Computation for Biomedicine and Neuroscience (IWINAC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10337))

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Abstract

The paper introduces a method of digital image processing for visually impaired people with central vision field loss. The method is based on image pixels relocation from the “blind zone” outside of its limits, and has been implemented within the CImagenMDI library. Transformed visual inputs are then used within the assistive tool with the aim to support a patient when performing everyday activities at work and home.

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Acknowledgements

This research was carried out within the PERVISION project, which has been supported by the Asociación de Innovaciones Tecnológicas en Oftalmología (AITO), Spain. We would also like to thank the Topcon® for the permission to use their equipment for the microperimetry test, as well as the Ophthalmology Department of the University Hospital of Albacete (SESCAM), and the members of the CRAB research group of the UCLM.

Author information

Authors and Affiliations

  1. University of Castilla-La Mancha, Albacete, Spain

    Marina V. Sokolova, Francisco J. Gómez & Miguel Ángel Fernández

  2. Southwest State University, Kursk, Russia

    Marina V. Sokolova

  3. University Hospital of Albacete, Albacete, Spain

    Jose Manuel Ortiz Egea

  4. MARPE Opticos, Albacete, Spain

    Adoración Pérez Andrés

Authors
  1. Marina V. Sokolova
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  2. Francisco J. Gómez
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  3. Jose Manuel Ortiz Egea
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  4. Miguel Ángel Fernández
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  5. Adoración Pérez Andrés
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Corresponding author

Correspondence to Marina V. Sokolova .

Editor information

Editors and Affiliations

  1. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    Félix de la Paz López

  4. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    Javier Toledo Moreo

  5. The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

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Sokolova, M.V., Gómez, F.J., Ortiz Egea, J.M., Fernández, M.Á., Pérez Andrés, A. (2017). Towards Assistive Solutions for People with Central Vision Loss. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Natural and Artificial Computation for Biomedicine and Neuroscience. IWINAC 2017. Lecture Notes in Computer Science(), vol 10337. Springer, Cham. https://doi.org/10.1007/978-3-319-59740-9_22

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  • DOI: https://doi.org/10.1007/978-3-319-59740-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59739-3

  • Online ISBN: 978-3-319-59740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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