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r can have any value in the range [0 1].
3.2.4 Some Utility M-Functions for Intensity Transformations
In this section we develop two custom M-functions that incorporate various aspects of the intensity transformations introduced in the previous three sec- tions. We show the details of the co[r]

3.8 Segmentation by active contour
In computer vision, recognising objects often depends on identifying particular shapes in an image. For example suppose we are interested in the outlines of the clock faces. We might start by looking to see whether image edges will help - so we mi[r]

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CCD camera. Such a camera has, in place of the usual film, an array of photosites ; these are silicon electronic devices whose voltage output is proportional to the intensity of light falling on them.
For a camera attached to a computer, information from the photosites is then output to a suitable[r]

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Digital Image Processing: Image Enhancement Spatial Filtering - Duong Anh Duc includes Image Enhancement - Spatial Filtering; How to specify T; Smoothing Filters; Image smoothing by averaging (lowpass spatial filtering); Image Sharpening; High-boost filtering; Prewitt operators.

If cach cell encompasses only one point on the boundary, the error in each cell be- tween the original boundary and the rubber-band approximation at most would be ⁄2đ, where đ is the min[r]

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cent contributions in the subject focus more on the digital signal types, specially the higher-order digital signals, due to increasing usage of such types in many novel applications.
Automatic digital-signal-type identification techniques usually can be categorized in two mai[r]

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The aim of this research is to (1) identify flooded area by using digital image processing approach; (2) to build GIS database about inundated area according to water lev[r]

Digital Image Processing: Unitary Transforms - Duong Anh Duc present about Unitary Transforms; Energy conservation with unitary transforms; Karhunen-Loeve transform; Optimum energy concentration by KL transform; Basis images and eigenimages; Sirovich and Kirby method; Gender recognition using eigenf[r]

Indeed, signal, image, and video processing, computer vision, 3D modelling, and graphics technologies are nowa- days widely employed to capture, analyze, conserve, virtually or physically restore, document, classify, recognize, and render cultural artefacts. These include historic buil[r]

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these two situations, we first find the zero crossing positions and label them as “1” and all other pixels as “0”. We then multiply the resulting image by a measure of
the edge strength at each pixel. There are various measures for the edge strength
that are all based on the gradient as d[r]