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Interactive Image Colorization Using Laplacian Coordinates

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Book cover Computer Analysis of Images and Patterns (CAIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9257))

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Abstract

Image colorization is a modern topic in computer vision which aims at manually adding colors to grayscale images. Techniques devoted to colorize images differ in many fundamental aspects as they often require an excessive number of image scribbles to reach pleasant colorizations. In fact, spreading lots of scribbles in the whole image consists of a laborious task that demands great efforts from users to accurately set appropriate colors to the image. In this work we present a new framework that only requires a small amount of image annotations to perform the colorization. The proposed framework combines the high-adherence on image contours of the Laplacian Coordinates segmentation approach with a fast color matching scheme to propagate colors to image partitions. User can locally manipulate colored regions so as to further improve the segmentation and thus the colorization result. We attest the effectiveness of our approach through a set of practical applications and comparisons against existing colorization techniques.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Sciences, University of São Paulo (USP), São Carlos, SP, 13566-590, Brazil

    Wallace Casaca, Marilaine Colnago & Luis Gustavo Nonato

  2. School of Engineering, Brown University, 182 Hope St., Providence, RI, 02912, USA

    Wallace Casaca

Authors
  1. Wallace Casaca
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  2. Marilaine Colnago
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  3. Luis Gustavo Nonato
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Corresponding author

Correspondence to Wallace Casaca .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Casaca, W., Colnago, M., Nonato, L.G. (2015). Interactive Image Colorization Using Laplacian Coordinates. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_58

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  • DOI: https://doi.org/10.1007/978-3-319-23117-4_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23116-7

  • Online ISBN: 978-3-319-23117-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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