By Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek
While the sphere of desktop imaginative and prescient drives a lot of today’s electronic applied sciences and verbal exchange networks, the subject of colour has emerged only in the near past in such a lot computing device imaginative and prescient functions. the most wide works thus far on colour in computing device imaginative and prescient, this publication offers a whole set of instruments for operating with colour within the box of picture understanding.
Based at the authors’ extreme collaboration for greater than a decade and drawing at the newest pondering within the box of laptop technology, the booklet integrates issues from colour technology and computing device imaginative and prescient, sincerely linking theories, options, computing device studying, and purposes. the basic fundamentals, pattern functions, and downloadable models of the software program and knowledge units also are incorporated. transparent, thorough, and useful, Color in Computer Vision explains:
- Computer imaginative and prescient, together with color-driven algorithms and quantitative result of numerous state of the art methods
- Color technological know-how issues resembling colour platforms, colour mirrored image mechanisms, colour invariance, and colour constancy
- Digital photograph processing, together with part detection, characteristic extraction, photograph segmentation, and photo transformations
- Signal processing innovations for the advance of either photo processing and desktop learning
- Robotics and synthetic intelligence, together with such subject matters as supervised studying and classifiers for item and scene categorization Researchers and pros in computing device technological know-how, laptop imaginative and prescient, colour technological know-how, electric engineering, and sign processing will methods to enforce colour in machine imaginative and prescient functions and achieve perception into destiny advancements during this dynamic and increasing field.
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Additional resources for Color in Computer Vision: Fundamentals and Applications
The removal of specularities allowed for improved segmentation algorithms [29, 28]. Throughout this book, we see several applications of the DRM, such as color constancy, photometric invariant feature computation, and color image segmentation. 3 Kubelka–Munk Model An older model from physics is the well-known Kubelka–Munk theory of light transfer. The model essentially captures the same aspects of Shafer’s DRM model. However, it provides a better background with established experimental work, as well as better understanding of the physical principles involved in light reﬂection by materials.
3 Chromatic Properties of the Visual System When put in context of other colors, however, the appearance is different and dependent on the exact deﬁnition of the surrounding colors. Two important spatial interactions are mentioned here, which inﬂuence color perception, contrast, and assimilation. In contrast effects, the difference between a color and its surround is enhanced so that the two will look more different. The effect can be interpreted as an induction effect, whereby the color complementary to that of the surround is induced into the center.
If we go out to buy a can of red paint to match the color of a tomato we saw earlier that day, chances are very high that the two colors will not match. Humans are far better in seeing differences between colors (relative color) than in memorizing absolute colors. Early measurements of chromatic discrimination thresholds  have laid the basis for the developments of a perceptually uniform color space (CIELAB), and the derivation of mathematical formulae to quantify color differences . The latter are abundantly used in industry.