Titlebook: Digital Image Processing; An Algorithmic Intro Wilhelm Burger,Mark James Burge Textbook 20081st edition Springer-Verlag London 2008 Digital

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Detecting Simple Curves,on at every position in the image. In the following sections, we explain how to decide (for example, by using a threshold operation on the edge strength) if a curve is actually present at a given image location. The result of this process is generally represented as a binary .. Edge maps are conside

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Infinitesimal

Color Images,printing. Color perception is a fascinating and complicated phenomenon that has occupied the interest of scientists, psychologists, philosophers, and artists for hundreds of years [88, 92]. In this chapter, we focus on those technical aspects of color that are most important for working with digital

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The Discrete Cosine Transform (DCT),se where the original signal was strictly real-valued. The reason is that neither the real nor the imaginary part of the Fourier spectrum alone is sufficient to represent (i. e., reconstruct) the signal completely. In other words, the corresponding cosine (for the real part) or sine functions (for t

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Geometric Operations,ch pixel and thus the geometry of the image remains the same. The purpose of geometric operations, which are discussed in this chapter, is to deform an image by altering its geometry. Typical examples are shifting, rotating, or scaling images, as shown in Fig. 16.1. Geometric operations are frequent

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Corner Detection, in machine vision, where they belong to the small set of features referred to as “robust”. Robust features are those that, for the most part, do not arise accidentally in 3D scenes and furthermore can be relatively consistently and accurately located under a wide range of viewing angles and lighting conditions.

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