Titlebook: Machine Vision; Automated Visual Ins Jürgen Beyerer,Fernando Puente León,Christian Fres Book 20161st edition Springer-Verlag Berlin Heidelb

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书目名称Machine Vision影响因子(影响力)




书目名称Machine Vision影响因子(影响力)学科排名




书目名称Machine Vision网络公开度




书目名称Machine Vision网络公开度学科排名




书目名称Machine Vision被引频次




书目名称Machine Vision被引频次学科排名




书目名称Machine Vision年度引用




书目名称Machine Vision年度引用学科排名




书目名称Machine Vision读者反馈




书目名称Machine Vision读者反馈学科排名

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Methods of Image AcquisitionThis chapter covers different methods for image acquisition in automated visual inspection. Selecting the appropriate acquisition method depends on the properties of interest of the investigated object (Fig. 7.1):

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Morphological Image ProcessingMorphological methods used in the algebra of sets can be used for morphological image processing. They were introduced by Matheron and Serra under the term ‘Mathematical Morphology’ [12, 16, 17]. Here, image signals are considered to be point sets and morphological filters are operations manipulating these sets.

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A Mathematical FoundationsThe intercept theorem [1,2] is an important principle for constructing the optical paths in the model of geometric optics (Chap. 3).

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Radiometrysible light is only a part of the whole electromagnetic spectrum (see Sec. 2.1.1). The respective wavelengths range from about 380 nm to 780 nm. Of course, physical measurements of intensity, power, etc., can be obtained for the whole electromagnetic spectrum without respect to the human eye, as is done in the domain of . or ..