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Feature selection in image analysis: a survey

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Abstract

Image analysis is a prolific field of research which has been broadly studied in the last decades, successfully applied to a great number of disciplines. Since the apparition of Big Data, the number of digital images is explosively growing, and a large amount of multimedia data is publicly available. Not only is it necessary to deal with this increasing number of images, but also to know which features extract from them, and feature selection can help in this scenario. The goal of this paper is to survey the most recent feature selection methods developed and/or applied to image analysis, covering the most popular fields such as image classification, image segmentation, etc. Finally, an experimental evaluation on several popular datasets using well-known feature selection methods is presented, bearing in mind that the aim is not to provide the best feature selection method, but to facilitate comparative studies for the research community.

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Notes

  1. http://www.image-net.org/challenges/LSVRC/.

  2. https://www.cs.waikato.ac.nz/ml/weka/downloading.html.

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Acknowledgements

This research has been financially supported in part by European Union FEDER funds, by the Spanish Ministerio de Economía y Competitividad (research project TIN2015-65069-C2), by the Consellería de Industria of the Xunta de Galicia (research project GRC2014/035), and by the Principado de Asturias (research project IDI-2018-000176). Financial support from the Xunta de Galicia (Centro singular de investigación de Galicia accreditation 2016–2019) and the European Union (European Regional Development Fund—ERDF), is gratefully acknowledged (research project ED431G/01). We are particularly grateful to Brais Cancela and Amparo Alonso-Betanzos for our stimulating discussions and their comments on the manuscript.

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  1. Department of Computer Science, Universidade da Coruña, CITIC, Campus de Elviña s/n, 15071, A Coruña, Spain

    Verónica Bolón-Canedo

  2. Department of Computer Science, Universidad de Oviedo, Campus de Gijón s/n, 33203, Gijón, Spain

    Beatriz Remeseiro

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Bolón-Canedo, V., Remeseiro, B. Feature selection in image analysis: a survey. Artif Intell Rev 53, 2905–2931 (2020). https://doi.org/10.1007/s10462-019-09750-3

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