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Concise Computer Vision: An Introduction into Theory and by Reinhard Klette

By Reinhard Klette

This textbook presents an available basic creation to the fundamental issues in laptop imaginative and prescient. Classroom-tested programming routines and evaluation questions also are provided on the finish of every bankruptcy. positive aspects: offers an creation to the fundamental notation and mathematical thoughts for describing a picture and the foremost innovations for mapping a picture into a picture; explains the topologic and geometric fundamentals for analysing picture areas and distributions of photo values and discusses deciding on styles in a picture; introduces optic stream for representing dense movement and numerous subject matters in sparse movement research; describes distinctive techniques for picture binarization and segmentation of nonetheless photographs or video frames; examines the fundamental elements of a working laptop or computer imaginative and prescient approach; stories diverse ideas for vision-based 3D form reconstruction; incorporates a dialogue of stereo matchers and the phase-congruency version for photograph beneficial properties; provides an creation into category and learning.

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Additional resources for Concise Computer Vision: An Introduction into Theory and Algorithms

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This section provides time-efficient methods that you may consider for preprocessing your data prior to subsequent image analysis. 1 Gradation Functions We transform an image I into an image Inew of the same size by mapping a grey level u at pixel location p in I by a gradation function g onto a grey level v = g(u) at the same pixel location p in Inew . Because the change only depends on value u at location p, we also speak about a point operator defined by a gradation function g. If the goal is that Inew satisfies some properties defined in terms of its histogram, then we speak about a histogram transform.

E. 43) defines the intensity of colour or grey level q. The HSI Space Consider a plane that cuts the RGB cube orthogonally to its greylevel diagonal, with q = (R, G, B) incident with this plane but not on the diagonal (see also Fig. 33). In an abstract sense, we represent the resulting cut by a disk, ignoring the fact that cuts of such a plane with the cube are actually simple polygons. See Fig. 31. For the disk, we fix one colour for reference; this is Red in Fig. 31. The location of q in the disk is uniquely defined by an angle H (the hue) and a scaled distance S (the saturation) from the intersecting grey-level diagonal of the RGB cube.

Tristimulus Values The CIE (Commission Internationale de l’Eclairage = International Commission on Illumination) has defined colour standards since the 1930s. A light source creates an energy distribution L(λ) for the visible spectrum for wavelengths 380 ≤ λ ≤ 780 of monochromatic light. See Fig. 25, left, for an example. 3 Colour and Colour Images 29 Fig. 25 Left: Sketch of an energy distribution curve L(λ) of an incandescent house lamp, for wavelengths λ between 380 nm and 780 nm for monochromatic light.

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