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Feature-Based Image Compression

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10751))

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Abstract

The EyeDee™ embedded eye tracking solution developed by SuriCog is the world’s first innovative solution using the eye as a real-time mobile digital cursor, while maintaining full mobility. The system consists in a wearable device capturing images on the human’s eye and sending these images over a transmission medium (wire/wireless transmission). One important request of this system is the real-time transmission of the captured images, along with low-power, low-heat, low-MIPS requirements. This work is concentrated around an improvement of the ROI (Region of Interest – region containing image of the human’s pupil) image compression performance achieved via extra information removal. The feature based compression lies on ROI image blocks classification, implemented using a neural network.

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Author information

Authors and Affiliations

  1. SuriCog, 130 Rue de Lourmel, 75015, Paris, France

    Pavel Morozkin & Marc Swynghedauw

  2. Institut Supérieur d’Electronique de Paris, 28 Rue Notre Dame des Champs, 75006, Paris, France

    Pavel Morozkin & Maria Trocan

Authors
  1. Pavel Morozkin
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  2. Marc Swynghedauw
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  3. Maria Trocan
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Corresponding author

Correspondence to Pavel Morozkin .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Morozkin, P., Swynghedauw, M., Trocan, M. (2018). Feature-Based Image Compression. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_43

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  • DOI: https://doi.org/10.1007/978-3-319-75417-8_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75416-1

  • Online ISBN: 978-3-319-75417-8

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