By Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek
While the sphere of laptop imaginative and prescient drives lots of today’s electronic applied sciences and communique networks, the subject of colour has emerged just recently in so much machine imaginative and prescient purposes. some of the most huge works thus far on colour in computing device imaginative and prescient, this ebook presents a whole set of instruments for operating with colour within the box of photograph understanding.
Based at the authors’ severe collaboration for greater than a decade and drawing at the most up-to-date considering within the box of machine technology, the booklet integrates issues from colour technological know-how and machine imaginative and prescient, essentially linking theories, concepts, computing device studying, and purposes. the elemental fundamentals, pattern purposes, and downloadable types of the software program and knowledge units also are integrated. transparent, thorough, and useful, Color in Computer imaginative and prescient explains:
- Computer imaginative and prescient, together with color-driven algorithms and quantitative result of numerous cutting-edge methods
- Color technological know-how issues corresponding to colour platforms, colour mirrored image mechanisms, colour invariance, and colour constancy
- Digital snapshot processing, together with facet detection, characteristic extraction, picture segmentation, and picture transformations
- Signal processing ideas for the improvement of either photo processing and desktop learning
- Robotics and synthetic intelligence, together with such issues as supervised studying and classifiers for item and scene categorization Researchers and pros in desktop technology, laptop imaginative and prescient, colour technological know-how, electric engineering, and sign processing will how to enforce colour in desktop imaginative and prescient purposes and achieve perception into destiny advancements during this dynamic and increasing field.
Chapter 1 creation (pages 1–9):
Chapter 2 colour imaginative and prescient (pages 11–25): via Marcel P. Lucassen
Chapter three colour snapshot Formation (pages 26–45):
Chapter four Pixel?Based Photometric Invariance (pages 47–68):
Chapter five Photometric Invariance from colour Ratios (pages 69–80): With contributions by means of Cordelia Schmid
Chapter 6 Derivative?Based Photometric Invariance (pages 81–112): With contributions by way of Rein van den Boomgaard and Arnold W. M. Smeulders
Chapter 7 Photometric Invariance via computer studying (pages 113–134): With contributions through Jose M. Alvarez and Antonio M. Lopez
Chapter eight Illuminant Estimation and Chromatic model (pages 135–142):
Chapter nine colour fidelity utilizing Low?level beneficial properties (pages 143–151):
Chapter 10 colour fidelity utilizing Gamut?Based tools (pages 152–160):
Chapter eleven colour fidelity utilizing laptop studying (pages 161–171):
Chapter 12 evaluate of colour fidelity tools (pages 172–186):
Chapter thirteen colour characteristic Detection (pages 187–220): With contributions by way of Arnold W. M. Smeulders and Andrew D. Bagdanov
Chapter 14 colour characteristic Description (pages 221–243): With contributions through Gertjan J. Burghouts
Chapter 15 colour picture Segmentation (pages 244–268): With contributions via Gertjan J. Burghouts
Chapter sixteen item and Scene acceptance (pages 269–286): With contributions by way of Koen E. A. van de Sande and Cees G. M. Snoek
Chapter 17 colour Naming (pages 287–317): With contributions through Robert Benavente, Maria Vanrell, Cordelia Schmid, Ramon Baldrich, Jakob Verbeek and Diane Larlus
Chapter 18 Segmentation of Multispectral pictures (pages 318–338): With contributions through Harro M. G. Stokman
Read Online or Download Color in Computer Vision: Fundamentals and Applications PDF
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Additional resources for Color in Computer Vision: Fundamentals and Applications
The model focuses on the color aspects of light reﬂection and has only limited usage for geometry recovery of scenes. The model assumes a single light source in the scene. It separates reﬂectance into surface body reﬂectance and interface reﬂectance. The model is valid for the class of inhomogeneous materials, which covers a wide range of materials such as wood, paints, papers, and plastics (but excludes homogeneous 29 3 Color Image Formation materials such as metals). The DRM is the summation of the body reﬂectance (superscript b) and the interface reﬂectance (superscript i): f c (x) = mb (x) s (λ, x) e (λ)ρ c (λ) dλ + mi (x) ω i (λ) e (λ)ρ c (λ) dλ.
15) Using this model, perfectly diffuse surfaces are modeled by substituting i(·) = 0, while perfect mirroring of the light source is modeled by substituting i(·) = 1. In reality, i(·) will assume a value somewhere in between 0 and 1, which results in the spectral color E(λ), which is an additive mixture of the color of the light source and the perfectly diffuse body reﬂectance color, similar as in the DRM model. Because the 3D coordinates are projected onto a 2D image plane, the vectors n, s, and v depend on the position in the image.
The degree of color constancy can be quantiﬁed using a constancy index ranging between 0 (no constancy at all) and 1 (perfect constancy). Foster  tabulated values for the constancy index for some 30 different experimental studies, showing widely varying values. Imperfect constancy implies that a change in the color of the illuminant is not fully discounted for by the visual system, which results in noticeable shifts in object colors. 4 presents a demonstration of color constancy. 4a shows a simulated change in the color of the global illuminant acting on the whole image.