Titlebook: Digital and Discrete Geometry; Theory and Algorithm Li M. Chen Book 2014 Springer International Publishing Switzerland 2014 Cloud Data Proc

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Shape Similarity Matching Queries example is to measure the distance between two points as we discussed in Chap. 3. In this chapter, we cover basic geometric measurements including curve length, surface area, and solid volumes in classical topics of geometry..The second main topic of this chapter is geometric computing, using algor

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Alternative Image Description Techniqueslysis, one of the most important geometric data analysis methods. Third, we present mathematical transformations for data analysis. This chapter is highly related to concurrent data sciences from theoretical perspectives. We focus on the practical methods of geometric data processing in the next cha

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Alternative Image Description Techniquess generally as: Given a set of . data points . in .-dimensional space,. ., how do we find the geometric structures of the sets or how do we use the geometric properties in real data processing? Geometric data representation, image segmentation, and object thinning are some of the most successful app

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Shape Analysis in Medical Image Analysisf overview of current development of computational topology that overlaps digital topology. Second, we introduce digital Gaussian curvatures and prove the digital form of the Gauss-Bonnet theorem. The new formula that calculates genus is . where . . indicates the set of surface-points, each of which

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https://doi.org/10.1007/978-3-642-54203-9in using Euler characteristic to analyze digital curves and surfaces. For the other two important problems related to discrete and digital topology: Jordan curve theorem and digital genus computation, we will discuss these in Chaps. 14 and 15.