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Image Features Extraction, Selection and Fusion for Computer Vision

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Image Feature Detectors and Descriptors

Part of the book series: Studies in Computational Intelligence ((SCI,volume 630))

Abstract

This chapter addresses many problems: different types of sensors, systems and methods from the literature are briefly revised, in order to give a recipe for designing intelligent vehicle systems based on computer vision. Many computer vision or related problems are addressed, like segmentation, features extraction and selection, fusion and classification. Existing solutions are investigated and three different data-bases are presented to perform typical experiments. Features extraction is aimed for finding pertinent features to encode information about possible obstacles from the road. Feature selection schemes are further used to compact the feature vector in order to decrease the computational time. Finally, several approaches to fuse visible and infrared images are used to increase the accuracy of the monomodal systems.

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Author information

Authors and Affiliations

  1. Communication Department, Technical University of Cluj-Napoca, 400027, Cluj, Romania

    Anca Apatean

  2. PSI Department, INSA Rouen, Rouen, France

    Alexandrina Rogozan & Abdelaziz Bensrhair

Authors
  1. Anca Apatean
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  2. Alexandrina Rogozan
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  3. Abdelaziz Bensrhair
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Corresponding author

Correspondence to Anca Apatean .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Luleå University of Technology, Luleå, Sweden

    Ali Ismail Awad

  2. Image and Video Processing Lab, Faculty, South Valley University, Qena, Egypt

    Mahmoud Hassaballah

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Apatean, A., Rogozan, A., Bensrhair, A. (2016). Image Features Extraction, Selection and Fusion for Computer Vision. In: Awad, A., Hassaballah, M. (eds) Image Feature Detectors and Descriptors . Studies in Computational Intelligence, vol 630. Springer, Cham. https://doi.org/10.1007/978-3-319-28854-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-28854-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28852-9

  • Online ISBN: 978-3-319-28854-3

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